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  • 1. A. Alkhamisi, Mahdi
    et al.
    Shukur, Ghazi
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    The Effect of Fat-Tailed Error Terms on the Properties of the Systemwise RESET Test2008Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 35, nr 1, s. 101-113Artikkel i tidsskrift (Fagfellevurdert)
  • 2.
    Albing, Malin
    et al.
    Department of Mathematics, Luleå University of Technology.
    Vännman, Kerstin
    Department of Mathematics, Luleå University of Technology.
    Elliptical safety region plots for Cpk2011Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 38, nr 6, s. 1169-1187Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The process capability index C pk is widely used when measuring the capability of a manufacturing process. A process is defined to be capable if the capability index exceeds a stated threshold value, e.g. C pk >4/3. This inequality can be expressed graphically using a process capability plot, which is a plot in the plane defined by the process mean and the process standard deviation, showing the region for a capable process. In the process capability plot, a safety region can be plotted to obtain a simple graphical decision rule to assess process capability at a given significance level. We consider safety regions to be used for the index C pk . Under the assumption of normality, we derive elliptical safety regions so that, using a random sample, conclusions about the process capability can be drawn at a given significance level. This simple graphical tool is helpful when trying to understand whether it is the variability, the deviation from target, or both that need to be reduced to improve the capability. Furthermore, using safety regions, several characteristics with different specification limits and different sample sizes can be monitored in the same plot. The proposed graphical decision rule is also investigated with respect to power.

  • 3. Albing, Malin
    et al.
    Vännman, Kerstin
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Matematiska vetenskaper.
    Elliptical safety region plots for Cpk2011Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 38, nr 6, s. 1169-1187Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The process capability index Cpk is widely used when measuring the capability of a manufacturing process. A process is defined to be capable if the capability index exceeds a stated threshold value, e.g. Cpk4/3. This inequality can be expressed graphically using a process capability plot, which is a plot in the plane defined by the process mean and the process standard deviation, showing the region for a capable process. In the process capability plot, a safety region can be plotted to obtain a simple graphical decision rule to assess process capability at a given significance level. We consider safety regions to be used for the index Cpk. Under the assumption of normality, we derive elliptical safety regions so that, using a random sample, conclusions about the process capability can be drawn at a given significance level. This simple graphical tool is helpful when trying to understand whether it is the variability, the deviation from target, or both that need to be reduced to improve the capability. Furthermore, using safety regions, several characteristics with different specification limits and different sample sizes can be monitored in the same plot. The proposed graphical decision rule is also investigated with respect to power

  • 4. Albing, Malin
    et al.
    Vännman, Kerstin
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Matematiska vetenskaper.
    Skewed zero-bound distributions and process capability indices for upper specifications2009Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 36, nr 2, s. 205-221Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A common practical situation in process capability analysis, which is not well developed theoretically, is when the quality characteristic of interest has a skewed distribution with a long tail towards relatively large values and an upper specification limit only exists. In such situations it is not uncommon that the smallest possible value of the characteristic is 0 and this also is the best value to obtain. Hence a target value 0 is assumed to exist. We investigate a new class of process capability indices for this situation. Two estimators of the proposed index are studied and the asymptotic distributions of these estimators are derived. Furthermore we suggest a decision procedure useful when drawing conclusions about the capability at a given significance level, based on the estimated indices and their asymptotic distributions. A simulation study is also performed, assuming that the quality characteristic is Weibull distributed, to investigate the true significance level when the sample size is finite.

  • 5. Alkamisi, M. A.
    et al.
    Shukur, Ghazi
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    Bayesian Analysis of a Linear Mixed Model with AR(p) errors Via MCMC2005Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 32, nr 7, s. 741-755Artikkel i tidsskrift (Fagfellevurdert)
  • 6. Almasri, Abdullah
    et al.
    Locking, Håkan
    Shukur, Ghazi
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    Testing for climate warming in Sweden during 1850-1999, using wavelets analysis2008Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 35, nr 4, s. 431-443Artikkel i tidsskrift (Fagfellevurdert)
  • 7. Arvidsson, M
    et al.
    Kammerlind, Peter
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Kvalitetsteknik.
    Hynen, A
    Chalmers Univ Technol, Dept Total Qual Management, S-41296 Gothenburg, Sweden Linkoping Univ, S-58183 Linkoping, Sweden ABB Corp Res, Baden, Switzerland.
    Bergman, B
    Chalmers Univ Technol, Dept Total Qual Management, S-41296 Gothenburg, Sweden Linkoping Univ, S-58183 Linkoping, Sweden ABB Corp Res, Baden, Switzerland.
    Identification of factors influencing dispersion in split-plot experiments2001Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 28, nr 3-4, s. 269-283Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    As split-plot designs are commonly used in robust design it is important to identify factors in these designs that influence the dispersion of the response variable. In this article, the Bergman-Hynen method, developed for identification of dispersion effects in unreplicated experiments, is modified to be used in the context of split-plot experiments. The modification of the Bergman-Hynen method enables identification of factors that influence specific variance components in unreplicated two-level fractional factorial split-plot experiments. An industrial example is used to illustrate the proposed method.

  • 8.
    Bayisa, Fekadu
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Yu, Jun
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Model-based computed tomography image estimation: partitioning approach2019Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532Artikkel i tidsskrift (Annet (populærvitenskap, debatt, mm))
    Abstract [en]

    There is a growing interest to get a fully MR based radiotherapy. The most important development needed is to obtain improved bone tissue estimation. The existing model-based methods perform poorly on bone tissues. This paper was aimed at obtaining improved bone tissue estimation. Skew-Gaussian mixture model and Gaussian mixture model were proposed to investigate CT image estimation from MR images by partitioning the data into two major tissue types. The performance of the proposed models was evaluated using the leaveone-out cross-validation method on real data. In comparison with the existing model-based approaches, the model-based partitioning approach outperformed in bone tissue estimation, especially in dense bone tissue estimation.

  • 9.
    Berhe, Leakemariam
    et al.
    Wondo Genet College of Forestry and Natural Resources, Hawassa University, Awassa, Ethiopia.
    Arnoldsson, Göran
    Umeå universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Ds-optimal designs for Kozak's tree taper model2011Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 38, nr 5, s. 1087-1102Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this work, we study Ds-optimal design for Kozak's tree taper model. The approximate Ds-optimal designs are found invariant to tree size and hence create a ground to construct a general replication-free Ds-optimal design. Even though the designs are found not to be dependent on the parameter value p of the Kozak's model, they are sensitive to the stimes1 subset parameter vector values of the model. The 12 points replication-free design (with 91% efficiency) suggested in this study is believed to reduce cost and time for data collection and more importantly to precisely estimate the subset parameters of interest.

  • 10.
    Ciavolino, E.
    et al.
    Dipartimento di Filosofia e Scienze Sociali, Università del Salento, Lecce, Italy.
    Jörn Dahlgaard, Jens
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Kvalitetsteknik. Linköpings universitet, Tekniska högskolan.
    Simultaneous Equation Model based on the generalized maximum entropy for studying the effect of management factors on enterprise performance2009Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 36, nr 7, s. 801-815Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The aim of this paper is to study the effect of management factors on enterprise performance, considering a survey that the University Consortium in Engineering for Quality and Innovation has led. The relationships between management factors and enterprise performance are formalized by a Simultaneous Equation Model based on the generalized maximum entropy (GME) estimation method. The format of this paper is as follows. In Section 2, the data collected, the questionnaire evaluation, and the management model analytical formulation are introduced. In Section 3, the GME formulation is specified, showing the main characteristics of the estimation method. In Section 4, the results and a comparison among GME, partial least squares (PLS), and maximum likelihood estimation (MLE) is shown. In Section 5, concluding remarks are discussed.

  • 11.
    Fackle-Fornius, Ellinor
    et al.
    Stockholm University, Sweden .
    Wänström, Linda
    Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Tekniska högskolan.
    Minimax D-optimal designs of contingent valuation experiments: willingness to pay for environmentally friendly clothes2014Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 41, nr 4, s. 895-908Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper demonstrates how to plan a contingent valuation experiment to assess the value of ecologically produced clothes. First, an appropriate statistical model (the trinomial spike model) that describes the probability that a randomly selected individual will accept any positive bid, and if so, will accept the bid A, is defined. Secondly, an optimization criterion that is a function of the variances of the parameter estimators is chosen. However, the variances of the parameter estimators in this model depend on the true parameter values. Pilot study data are therefore used to obtain estimates of the parameter values and a locally optimal design is found. Because this design is only optimal given that the estimated parameter values are correct, a design that minimizes the maximum of the criterion function over a plausable parameter region (i.e. a minimax design) is then found.

  • 12.
    Fackle-Fornius, Ellinor
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Wänström, Linda
    Minimax D-optimal designs of contingent valuation experiments: willingness to pay for environmentally friendly clothes2014Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 41, nr 4, s. 895-908Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper demonstrates how to plan a contingent valuation experiment to assess the value of ecologically produced clothes. First, an appropriate statistical model (the trinomial spike model) that describes the probability that a randomly selected individual will accept any positive bid, and if so, will accept the bid A, is defined. Secondly, an optimization criterion that is a function of the variances of the parameter estimators is chosen. However, the variances of the parameter estimators in this model depend on the true parameter values. Pilot study data are therefore used to obtain estimates of the parameter values and a locally optimal design is found. Because this design is only optimal given that the estimated parameter values are correct, a design that minimizes the maximum of the criterion function over a plausable parameter region (i.e. a minimax design) is then found.

  • 13.
    Ghilagaber, Gebrenegus
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Munezero, Parfait
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Bayesian Change-point Modelling of the Effects of 3-points-for-a-win Rule in Football2019Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We examine the effects of the 3-points-for-a-win (3pfaw) rule in the football world. Data that form the basis of our analyses come from seven leagues around the world (Albania, Brazil, England, Germany, Poland, Romania, and Scotland) and consist of mean goals and proportions of decided matches over a period of about six years before- and about seven years after the introduction of the rule in the respective leagues. Bayesian change-point analyses and Shiryaev-Roberts tests show that the rule had no effects on the mean goals but, indeed, had increasing effects on the proportions of decided matches in most of the leagues studied. This, in turn, implies that while the rule has given teams the incentive to aim at winning matches, such aim was not achieved by scoring excess goals. Instead, it was achieved by scoring enough goals in order to win and, at the same time, defending enough in order not to lose. Our results are in accordance with recent findings on comparing the values of attack and defense - that, in top-level football, not conceding a goal is more valuable than scoring a single goal.

  • 14.
    Hacker, R Scott
    et al.
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    Hatemi-J, Abdulnasser
    Optimal Lag Length Choice in Stable and Unstable VAR Models under Situations of Homoscedasticity and ARCH2008Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 35, nr 6, s. 601-615Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The performance of different information criteria - namely Akaike, corrected Akaike (AICC), Schwarz-Bayesian (SBC), and Hannan-Quinn - is investigated so as to choose the optimal lag length in stable and unstable vector autoregressive (VAR) models both when autoregressive conditional heteroscedasticity (ARCH) is present and when it is not. The investigation covers both large and small sample sizes. The Monte Carlo simulation results show that SBC has relatively better performance in lag-choice accuracy in many situations. It is also generally the least sensitive to ARCH regardless of stability or instability of the VAR model, especially in large sample sizes. These appealing properties of SBC make it the optimal criterion for choosing lag length in many situations, especially in the case of financial data, which are usually characterized by occasional periods of high volatility. SBC also has the best forecasting abilities in the majority of situations in which we vary sample size, stability, variance structure (ARCH or not), and forecast horizon (one period or five). frequently, AICC also has good lag-choosing and forecasting properties. However, when ARCH is present, the five-period forecast performance of all criteria in all situations worsens.

  • 15.
    Hacker, R. Scott
    et al.
    Jönköping Int Business Sch, Dept Econ, Jönköping, Sweden.
    Hatemi-J., Abdulnasser
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Optimal lag-length choice in stable and unstable VAR models under situations of homoscedasticity and ARCH2008Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 35, nr 6, s. 601-615Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The performance of different information criteria - namely Akaike, corrected Akaike (AICC), Schwarz-Bayesian (SBC), and Hannan-Quinn - is investigated so as to choose the optimal lag length in stable and unstable vector autoregressive (VAR) models both when autoregressive conditional heteroscedasticity (ARCH) is present and when it is not. The investigation covers both large and small sample sizes. The Monte Carlo simulation results show that SBC has relatively better performance in lag-choice accuracy in many situations. It is also generally the least sensitive to ARCH regardless of stability or instability of the VAR model, especially in large sample sizes. These appealing properties of SBC make it the optimal criterion for choosing lag length in many situations, especially in the case of financial data, which are usually characterized by occasional periods of high volatility. SBC also has the best forecasting abilities in the majority of situations in which we vary sample size, stability, variance structure (ARCH or not), and forecast horizon (one period or five). frequently, AICC also has good lag-choosing and forecasting properties. However, when ARCH is present, the five-period forecast performance of all criteria in all situations worsens.

  • 16.
    Holgersson, Thomas
    Högskolan i Jönköping.
    Testing for Multivariate Autocorrelation2004Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 31, nr 4, s. 379-395Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper concerns the problem of assessing autocorrelation of multivariate (i.e. systemwise) models. It is well known that systemwise diagnostic tests for autocorrelation often suffers from poor small sample properties in the sense that the true size overstates the nominal size. The failure of keeping control of the size usually stems from the fact that the critical values (used to decide the rejection area) originate from the slowly converging asymptotic null distribution. Another drawback of existing tests is that the power may be rather low if the deviation from the null is not symmetrical over the marginal models. In this paper we consider four quite different test techniques for autocorrelation. These are (i) Pillai's trace, (ii) Roy's largest root, (iii) the maximum F-statistic and (iv) the maximum t2 test. We show how to obtain control of the size of the tests, and then examine the true (small sample) size and power properties by means of Monte Carlo simulations.

  • 17.
    Holgersson, Thomas
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    Testing for Multivariate Autocorrelation2004Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 31, nr 4, s. 379-395Artikkel i tidsskrift (Fagfellevurdert)
  • 18.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Karlsson, Peter
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Three estimators of the Mahalanobis distance in high-dimensional data2012Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, nr 12, s. 2713-2720Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper treats the problem of estimating the Mahalanobis distance for the purpose of detecting outliersin high-dimensional data. Three ridge-type estimators are proposed and risk functions for deciding anappropriate value of the ridge coefficient are developed. It is argued that one of the ridge estimator hasparticularly tractable properties, which is demonstrated through outlier analysis of real and simulated data.

  • 19.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Karlsson, Peter
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Mansoor, Rashid
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Estimating mean-standard deviation ratios of financial data2012Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, nr 3, s. 657-671Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This article treats the problem of linking the relation between excess return and risk of financial assets when the returns follow a factor structure. The authors propose three different estimators and their consistencies are established in cases when the number of assets in the cross-section (n) and the number of observations over time (T) are of comparable size. An empirical investigation is conducted on the Stockholm stock exchange market where the mean-standard deviation ratio is calculated for small- mid- and large cap segments, respectively.

  • 20.
    Holgersson, Thomas
    et al.
    Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU.
    Karlsson, Peter S.
    Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU.
    Three estimators of the Mahalanobis distance in high-dimensional data2012Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, nr 12, s. 2713-2720Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper treats the problem of estimating the Mahalanobis distance for the purpose of detecting outliers in high-dimensional data. Three ridge-type estimators are proposed and risk functions for deciding an appropriate value of the ridge coefficient are developed. It is argued that one of the ridge estimator has particularly tractable properties, which is demonstrated through outlier analysis of real and simulated data.

  • 21.
    Holgersson, Thomas
    et al.
    Jönköping University.
    Karlsson, Peter S.
    Jönköping University.
    Mansoor, Rashid
    Jönköping University.
    Estimating mean-standard deviation ratios of financial data2012Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, nr 3, s. 657-671Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This article treats the problem of linking the relation between excess return and risk of financial assets when the returns follow a factor structure. The authors propose three different estimators and their consistencies are established in cases when the number of assets in the cross-section (n) and the number of observations over time (T) are of comparable size. An empirical investigation is conducted on the Stockholm stock exchange market where the mean-standard deviation ratio is calculated for small- mid- and large cap segments, respectively.

  • 22.
    Holgersson, Thomas
    et al.
    Linnéuniversitetet, Ekonomihögskolan (FEH), Institutionen för nationalekonomi och statistik (NS). Jönköping University.
    Nordström, Louise
    Jönköping University.
    Öner, Özge
    Jönköping University.
    Dummy Variables vs. Category-wise Models2014Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 41, nr 2, s. 233-241Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Empirical research frequently involves regression analysis with binary categorical variables, which are traditionally handled through dummy explanatory variables. This paper argues that separate category-wise models may provide a more logical and comprehensive tool for analysing data with binary categories. Exploring different aspects of both methods, we contrast the two with a Monte Carlo simulation and an empirical example to provide a practical insight.

  • 23.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Nordström, Louise
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Öner, Özge
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Dummy variables vs. category-wise models2014Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 41, nr 2, s. 233-241Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Empirical research frequently involves regression analysis with binary categorical variables, which are traditionally handled through dummy explanatory variables. This paper argues that separate category-wise models may provide a more logical and comprehensive tool for analysing data with binary categories. Exploring different aspects of both methods, we contrast the two with a Monte Carlo simulation and an empirical example to provide a practical insight.

  • 24.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Statistik.
    Nordström, Louise
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    Öner, Özge
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    On regression modelling with dummy variables versus separate regressions per group: comment on Holgersson et al.2016Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, nr 8, s. 1564-1565Artikkel i tidsskrift (Annet vitenskapelig)
  • 25.
    Holgersson, Thomas
    et al.
    Jönköping University.
    Öner, Özge
    Jönköping University.
    Nordström, Louise
    Jönköping University.
    On regression modelling with dummy variables versus separate regressions per group: comment on Holgersson et al.2016Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, nr 8, s. 1564-1565Artikkel i tidsskrift (Fagfellevurdert)
  • 26. Hussain, Shakir
    et al.
    Shukur, Ghazi
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    Estimation and Forecasting of Hospital Admission Due to Influenza: Planning for Winter Pressure. The Case of the West Midlands, UK2005Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 32, nr 3, s. 191-205Artikkel i tidsskrift (Fagfellevurdert)
  • 27.
    Johansson, Jan-Olof
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE).
    Modelling the surface structure of newsprint2000Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 27, nr 4, s. 425-438Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The Gibbs distribution is often used to model micro-textures. This includes a definition of a neighbourhood system. If a micro-texture contains a large-scale variation, the neighbourhood system will be large, which implies many parameters in the corresponding Gibbs distribution. The estimation of the parameters for such models will be difficult and time consuming. I suggest, in this paper, a separation of the micro-texture into a large-scale variation and a small-scale variation and model each source of variation with a Gibbs distribution. This method is applied on full-tone print of newsprint to model the variation caused by print mottle. In this application, the large-scale variation is mainly caused by fibre flocculation and clustering and the small-scale variation contains the variation of the fibres and fines on and between the clusters. The separate description of these two variations makes it possible to relate different kinds of paper qualities to the appropriate source of variation.

  • 28. Kibria, B. M. Golam
    et al.
    Månsson, Kristofer
    Shukur, Ghazi
    Linnéuniversitetet, Ekonomihögskolan (FEH), Institutionen för nationalekonomi och statistik (NS).
    Some Ridge Regression estimator for the zero-inflated Poisson model2013Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 40, nr 4, s. 721-735Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The zero inflated Poisson regression model is very common when analysing economic data that comes in the form of non-negative integers since it accounts for excess zeros and overdispersion of the dependent variable. However, a problem often encountered when analyzing economic data that has not been addressed for this model is multicollinearity. This paper proposes ridge regression estimators and some methods of estimating the ridge parameter k for the non-negative model. A simulation study has been conducted to compare the performance of the estimators. Both mean squared error (MSE) and mean absolute error (MAE) are considered as performance criterion. The simulation study shows that some estimators are better than the commonly used maximum likelihood estimator and some other ridge regression estimators. Based on the simulation study and an empirical application, some useful estimators are recommended for the practitioners.

  • 29.
    Kibria, B. M. Golam
    et al.
    Department of Mathematics and Statistics, Florida International University, Miami, Florida, USA.
    Shukur, Ghazi
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Månsson, Kristofer
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Economics, Finance and Statistics.
    Some ridge regression estimators for the zero-inflated Poisson model2013Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 40, nr 4, s. 721-735Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The zero-inflated Poisson regression model is commonly used when analyzing economic data that come in the form of non-negative integers since it accounts for excess zeros and overdispersion of the dependent variable. However, a problem often encountered when analyzing economic data that has not been addressed for this model is multicollinearity. This paper proposes ridge regression (RR) estimators and some methods for estimating the ridge parameter k for a non-negative model. A simulation study has been conducted to compare the performance of the estimators. Both mean squared error and mean absolute error are considered as the performance criteria. The simulation study shows that some estimators are better than the commonly used maximum-likelihood estimator and some other RR estimators. Based on the simulation study and an empirical application, some useful estimators are recommended for practitioners.

  • 30.
    Kulahci, Murat
    et al.
    Department of Industrial Engineering, Arizona State University, Tempe.
    Bisgaard, Søren
    Isenberg School of Management, University of Massachusetts Amherst, Eugene M. Isenberg School of Management, University of Massachusetts Amherst.
    A generalization of the alias matrix2006Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 33, nr 4, s. 387-395Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The investigation of aliases or biases is important for the interpretation of the results from factorial experiments. For two-level fractional factorials this can be facilitated through their group structure. For more general arrays the alias matrix can be used. This tool is traditionally based on the assumption that the error structure is that associated with ordinary least squares. For situations where that is not the case, we provide in this article a generalization of the alias matrix applicable under the generalized least squares assumptions. We also show that for the special case of split plot error structure, the generalized alias matrix simplifies to the ordinary alias matrix

  • 31.
    Kulahci, Murat
    et al.
    University of Wisconsin.
    Bisgaard, Søren
    Isenberg School of Management, University of Massachusetts Amherst, Eugene M. Isenberg School of Management, University of Massachusetts Amherst, University of Amsterdam.
    Switching-one-column follow-up experiments for Plackett-Burman designs2001Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 28, nr 8, s. 943-949Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Industrial experiments are frequently performed sequentially using two-level fractional factorial designs. In this context, a common strategy for the design of follow-up experiments is to switch the signs in one column. It is well known that this strategy, when applied to two-level fractional factorial resolution III designs, will clear the main effect, for which the switch was performed, from any confounding with any other two-factor interactions and will also clear all the two-factor interactions between that factor and the other main effects from any confounding with other two-factor interactions. In this article, we extend this result and show that this strategy applies to any orthogonal two-level resolution III design and therefore specifically to any two-level Plackett-Burman design.

  • 32.
    Kulahci, Murat
    et al.
    Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, Industriell Ekonomi.
    Tyssedal, John Sølve
    Department of Mathematical Sciences, The Norwegian University of Science and Technology, Trondheim.
    Split-plot designs for multistage experimentation2017Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 44, nr 3, s. 493-510Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Most of today’s complex systems and processes involve several stages through which input or the raw material has to go before the final product is obtained. Also in many cases factors at different stages interact. Therefore, a holistic approach for experimentation that considers all stages at the same time will be more efficient. However, there have been only a few attempts in the literature to provide an adequate and easy-to-use approach for this problem. In this paper, we present a novel methodology for constructing two-level split-plot and multistage experiments. The methodology is based on the Kronecker product representation of orthogonal designs and can be used for any number of stages, for various numbers of subplots and for different number of subplots for each stage. The procedure is demonstrated on both regular and nonregular designs and provides the maximum number of factors that can be accommodated in each stage. Furthermore, split-plot designs for multistage experiments with good projective properties are also provided.

  • 33.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Scale-Space Theory: A Basic Tool for Analysing Structures at Different Scales1994Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 21, s. 225-270Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    An inherent property of objects in the world is that they only exist as meaningful entities over certain ranges of scale. If one aims at describing the structure of unknown real-world signals, then a multi-scale representation of data is of crucial importance.

    This article gives a tutorial review of a special type of multi-scale representation, linear scale-space representation, which has been developed by the computer vision community in order to handle image structures at different scales in a consistent manner. The basic idea is to embed the original signal into a one-parameter family of gradually smoothed signals, in which the fine scale details are successively suppressed.

    Under rather general conditions on the type of computations that are to performed at the first stages of visual processing, in what can be termed the visual front end, it can be shown that the Gaussian kernel and its derivatives are singled out as the only possible smoothing kernels. The conditions that specify the Gaussian kernel are, basically, linearity and shift-invariance combined with different ways of formalizing the notion that structures at coarse scales should correspond to simplifications of corresponding structures at fine scales --- they should not be accidental phenomena created by the smoothing method. Notably, several different ways of choosing scale-space axioms give rise to the same conclusion.

    The output from the scale-space representation can be used for a variety of early visual tasks; operations like feature detection, feature classification and shape computation can be expressed directly in terms of (possibly non-linear) combinations of Gaussian derivatives at multiple scales. In this sense, the scale-space representation can serve as a basis for early vision.

    During the last few decades a number of other approaches to multi-scale representations have been developed, which are more or less related to scale-space theory, notably the theories of pyramids, wavelets and multi-grid methods. Despite their qualitative differences, the increasing popularity of each of these approaches indicates that the crucial notion of scaleis increasingly appreciated by the computer vision community and by researchers in other related fields.

    An interesting similarity with biological vision is that the scale-space operators closely resemble receptive field profiles registered in neurophysiological studies of the mammalian retina and visual cortex.

  • 34.
    Lindström, Fredrik
    et al.
    Försäkringskassan.
    Holgersson, Thomas
    Högskolan i Jönköping.
    Forecast mean squared error reductionin the VAR(1) process2009Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 36, nr 12, s. 1369-1384Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    When VAR models are used to predict future outcomes, the forecast error can be substantial. Through imposition of restrictions on the off-diagonal elements of the parameter matrix, however, the information in the process may be condensed to the marginal processes. In particular, if the cross-autocorrelations in the system are small and only a small sample is available, then such a restriction may reduce the forecast mean squared error considerably.

    In this paper, we propose three different techniques to decide whether to use the restricted or unrestricted model, i.e. the full VAR(1) model or only marginal AR(1) models. In a Monte Carlo simulation study, all three proposed tests have been found to behave quite differently depending on the parameter setting. One of the proposed tests stands out, however, as the preferred one and is shown to outperform other estimators for a wide range of parameter settings.

  • 35.
    Lindström, Fredrik
    et al.
    Försäkringskassan.
    Holgersson, Thomas
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    Forecast mean squared error reductionin the VAR(1) process2009Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 36, nr 12, s. 1369-1384Artikkel i tidsskrift (Fagfellevurdert)
  • 36.
    Mantalos, Panagiotis
    et al.
    Department of Statistics, Lund University, Lund, Sweden.
    Shukur, Ghazi
    Department of Economics, Jönköping International Business School, Jönköping University, Jönköping, Sweden.
    The effect of spillover on the Granger causality test2010Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 37, nr 9, s. 1473-1486Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, we investigate the properties of the Granger causality test in stationary and stable vector autoregressive models under the presence of spillover effects, that is, causality in variance. The Wald test and the WW test (the Wald test with White's proposed heteroskedasticity-consistent covariance matrix estimator imposed) are analyzed. The investigation is undertaken by using Monte Carlo simulation in which two different sample sizes and six different kinds of data-generating processes are used. The results show that the Wald test over-rejects the null hypothesis both with and without the spillover effect, and that the over-rejection in the latter case is more severe in larger samples. The size properties of the WW test are satisfactory when there is spillover between the variables. Only when there is feedback in the variance is the size of the WW test slightly affected. The Wald test is shown to have higher power than the WW test when the errors follow a GARCH(1,1) process without a spillover effect. When there is a spillover, the power of both tests deteriorates, which implies that the spillover has a negative effect on the causality tests.

  • 37.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Shukur, Ghazi
    Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU.
    The Effect of the Spillover on the Granger Causality Test 2010Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 37, nr 9, s. 1473-1486Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, we investigate the properties of the Granger causality test in stationary and stable vector autoregressive models under the presence of spillover effects, i.e., causality in variance. The Wald test and the WW test (the Wald test with White’s proposed heteroskedasticity-consistent covariance matrix estimator imposed) are analyzed. The investigation is undertaken by using Monte Carlo simulation in which two different sample sizes and six different kinds of data generating process are used. The results show that the Wald test overrejects the null hypothesis both with and without the spillover effect, and that the overrejection in the latter case is more severe in larger samples. The size properties of the WW test are satisfactory when there is spillover between the variables. Only when there is feedback in the variance is the size of the WW test slightly affected. The Wald test is shown to have higher power than the WW test when the errors follow a GARCH(1,1) process without a spillover effect. When there is spillover, the power of both tests deteriorates, which implies that the spillover has a negative effect on the causality tests.

  • 38.
    Mark, Sigyn
    et al.
    Högskolan Väst, Institutionen för ingenjörsvetenskap, Avd för lantmäteriteknik och matematik.
    Holm, Sture
    Göteborg University, Department of Mathematics.
    Test and prediction in factorial models with independent variance estimates2008Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 35, nr 7, s. 773-782Artikkel i tidsskrift (Fagfellevurdert)
  • 39.
    Mukherjee, Amitava
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Purkait, Barendra
    Simultaneous semi-sequential testing of dual alternatives for pattern recognition2011Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 38, nr 2, s. 399-419Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, we propose a new nonparametric simultaneous test for dual alternatives. Simultaneous tests for dual alternatives are used for pattern detection of arsenic contamination level in ground water. We consider two possible patterns, namely, monotone shift and an umbrella-type location alternative, as the dual alternatives. Pattern recognition problems of this nature are addressed in Bandyopadhyay et al. [5], stretching the idea of multiple hypotheses tests as in Benjamini and Hochberg [6]. In the present context, we develop an alternative approach based on contrasts that helps us to detect three underlying pattern much more efficiently. We illustrate the new methodology through a motivating example related to highly sensitive issue of arsenic contamination in ground water. We provide some Monte-Carlo studies related to the proposed technique and give a comparative study between different detection procedures. We also obtain some related asymptotic results.

  • 40.
    Månsson, Kristofer
    et al.
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Statistik.
    Kibria, B. M. Golam
    Florida International University.
    Shukur, Ghazi
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Statistik.
    A restricted Liu estimator for binary regression models and its application to an applied demand system2016Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, nr 6, s. 1119-1127Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this article, we propose a restricted Liu regression estimator (RLRE) for estimating the parameter vector, β, in the presence of multicollinearity, when the dependent variable is binary and it is suspected that β may belong to a linear subspace defined by =r. First, we investigate the mean squared error (MSE) properties of the new estimator and compare them with those of the restricted maximum likelihood estimator (RMLE). Then we suggest some estimators of the shrinkage parameter, and a simulation study is conducted to compare the performance of the different estimators. Finally, we show the benefit of using RLRE instead of RMLE when estimating how changes in price affect consumer demand for a specific product.

  • 41.
    Månsson, Kristofer
    et al.
    Jönköping University.
    Kibria, B.M. Golam
    Florida International University, USA.
    Shukur, Ghazi
    Linnéuniversitetet, Ekonomihögskolan (FEH), Institutionen för nationalekonomi och statistik (NS). Jönköping University.
    A restricted Liu estimator for binary regression models and its application to an applied demand system2016Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, nr 6, s. 1119-1127Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this article, we propose a restricted Liu regression estimator (RLRE) for estimating the parameter vector, β, in the presence of multicollinearity, when the dependent variable is binary and it is suspected that β may belong to a linear subspace defined by =r. First, we investigate the mean squared error (MSE) properties of the new estimator and compare them with those of the restricted maximum likelihood estimator (RMLE). Then we suggest some estimators of the shrinkage parameter, and a simulation study is conducted to compare the performance of the different estimators. Finally, we show the benefit of using RLRE instead of RMLE when estimating how changes in price affect consumer demand for a specific product.

  • 42. Pavlenko, Tatjana
    et al.
    Björkström, Anders
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Tillander, Annika
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Covariance structure approximation via glasso in high dimensional supervised classification2012Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, nr 8, s. 1643-1666Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Recent work has shown that the Lasso-based regularization is very useful for estimating the high-dimensional inverse covariance matrix. A particularly useful scheme is based on penalizing the l(1) norm of the off-diagonal elements to encourage sparsity. We embed this type of regularization into high-dimensional classification. A two-stage estimation procedure is proposed which first recovers structural zeros of the inverse covariance matrix and then enforces block sparsity by moving non-zeros closer to the main diagonal. We show that the block-diagonal approximation of the inverse covariance matrix leads to an additive classifier, and demonstrate that accounting for the structure can yield better performance accuracy. Effect of the block size on classification is explored, and a class of as ymptotically equivalent structure approximations in a high-dimensional setting is specified. We suggest a variable selection at the block level and investigate properties of this procedure in growing dimension asymptotics. We present a consistency result on the feature selection procedure, establish asymptotic lower an upper bounds for the fraction of separative blocks and specify constraints under which the reliable classification with block-wise feature selection can be performed. The relevance and benefits of the proposed approach are illustrated on both simulated and real data.

  • 43.
    Pavlenko, Tatjana
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Matematisk statistik.
    Björkström, Anders
    Stockholm Univ, Stockholm, Sweden.
    Tillander, Annika
    Stockholm Univ, Stockholm, Sweden.
    Covariance structure approximation via gLasso in high-dimensional supervised classification2012Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, nr 8, s. 1643-1666Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Recent work has shown that the Lasso-based regularization is very useful for estimating the high-dimensional inverse covariance matrix. A particularly useful scheme is based on penalizing the l(1) norm of the off-diagonal elements to encourage sparsity. We embed this type of regularization into high-dimensional classification. A two-stage estimation procedure is proposed which first recovers structural zeros of the inverse covariance matrix and then enforces block sparsity by moving non-zeros closer to the main diagonal. We show that the block-diagonal approximation of the inverse covariance matrix leads to an additive classifier, and demonstrate that accounting for the structure can yield better performance accuracy. Effect of the block size on classification is explored, and a class of as ymptotically equivalent structure approximations in a high-dimensional setting is specified. We suggest a variable selection at the block level and investigate properties of this procedure in growing dimension asymptotics. We present a consistency result on the feature selection procedure, establish asymptotic lower an upper bounds for the fraction of separative blocks and specify constraints under which the reliable classification with block-wise feature selection can be performed. The relevance and benefits of the proposed approach are illustrated on both simulated and real data.

  • 44.
    Rydén, Jesper
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Matematiska institutionen, Matematisk statistik.
    Alm, Sven Erick
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Matematiska institutionen, Matematisk statistik.
    The effect of interaction and rounding error in two-way ANOVA: example of impact on testing for normality2010Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 37, nr 10, s. 1695-1701Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A key issue in various applications of analysis of variance (ANOVA) is testing for the interaction and the interpretation of resulting ANOVA tables. In this note it is demonstrated that for a two-way ANOVA, whether interactions are incorporated or not may have a dramatic influence when considering the usual statistical tests for normality of residuals. The effect of numerical rounding is also discussed.

  • 45.
    Segerstedt, Bo
    et al.
    Umeå universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Nyquist, Hans
    Umeå universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    On the conditioning problem in generalized linear models1992Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 19, nr 4, s. 513-526Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    When weights are assigned to a data matrix, as in the iterative least squares estimator of a generalized linear model, the condition of the data matrix is changed. In this paper a geometrical approach to studying the mechanisms which determine the changed condition is introduced. Specifically, it is found that in some cases strong multicollinearities can be weakened or eliminated by the weights while in other cases the weights can induce an ill-conditioning.

  • 46.
    Shukur, Ghazi
    et al.
    Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU.
    Alkhamisi, Mahdi A.
    Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU.
    Bayesian Analysis of a Linear Mixed  Model with AR(p) errors Via MCMC2005Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 32, nr 7, s. 741-755Artikkel i tidsskrift (Fagfellevurdert)
  • 47.
    Shukur, Ghazi
    et al.
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    Almasri, Abdullah
    An Illustration of the Causality Relation between Government Spending and Revenue Using Wavelet Analysis on Finnish Data2003Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 30, nr 5, s. 571-584Artikkel i tidsskrift (Fagfellevurdert)
  • 48.
    Shukur, Ghazi
    et al.
    Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU.
    Almasri, Abdullah
    Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU.
    An Illustration of the Causality Relation between Government Spending and Revenue Using Wavelets Analysis on Finnish Data2003Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 30, s. 571-584Artikkel i tidsskrift (Fagfellevurdert)
  • 49.
    Shukur, Ghazi
    et al.
    Högskolan i Jönköping, Internationella Handelshögskolan, IHH, Nationalekonomi.
    Hatemi-J, Abdulanaser
    Multivariate-based causality tests of twin deficits in the US2002Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 29, nr 6, s. 817-824Artikkel i tidsskrift (Fagfellevurdert)
  • 50.
    Shukur, Ghazi
    et al.
    Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU.
    Hatemi-J, Abdulnasser
    A Multivariate Based Causality Test of Twin Deficits in US2002Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 29, s. 817-824Artikkel i tidsskrift (Fagfellevurdert)
12 1 - 50 of 65
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