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  • 1. Bjellerup, Mårten
    et al.
    Holgersson, Thomas
    Högskolan i Jönköping.
    A simple multivariate test for asymmetry2009In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 41, no 11, p. 1405-1416Article in journal (Refereed)
    Abstract [en]

    Since many macroeconomic models are linear, it is not desirable to use themwith an asymmetric dependent variable. In this article, we formulate aunivariate test for symmetry, based on the third central moment and extendit to a multivariate test; the test does not require modelling and it is robustagainst serial correlation, Autoregressive Conditional Heteroscedasticity(ARCH) and nonnormality. In the empirical application of the test it isfound that orthodox theory seem to be supported; consumption expendi-ture on durable goods is found to be symmetric while consumptionexpenditure on nondurable goods is asymmetric for the USA and the UK,with peaks being higher than troughs are deep. Also, the empiricalimportance of the choice between the univariate and the multivariate testfor possibly correlated series is underscored; the results from the twoapproaches  clearly  differ.  Given  the  widespread  practice  of  usingconsumption expenditure on nondurable goods as the dependent variablein linear models for the USA and the UK, our results might be noteworthy.

  • 2.
    Dai, Deliang
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Holgersson, Thomas
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Karlsson, Peter S.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Expected and unexpected values of Individual Mahalanobis Distances2017In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 46, no 18, p. 8999-9006Article in journal (Refereed)
    Abstract [en]

    This paper derives first-order sampling moments of individual Mahalanobis distances (MD) in cases when the dimension p of the variable is proportional to the sample size n. Asymptotic expected values when n, p → ∞ are derived under the assumption p/n → c, 0 ⩽ c < 1. It is shown that some types of standard estimators remain unbiased in this case, while others are asymptotically biased, a property that appears to be unnoticed in the literature. Second order moments are also supplied to give some additional insight to the matter.

  • 3.
    Florida, Richard
    et al.
    University of Toronto, Canada.
    Mellander, Charlotta
    Jönköping University.
    Holgersson, Thomas
    Jönköping University.
    Up in the air: the role of airports for regional economic development2015In: The annals of regional science, ISSN 0570-1864, E-ISSN 1432-0592, Vol. 54, no 1, p. 197-214Article in journal (Refereed)
    Abstract [en]

    Our research examines the role of airports in regional development. Specifically, we examine two things: (1) the factors associated with whether or not a metro will have an airport, and (2) the effect of airport activities on regional economic development. Based on multiple regression analysis for U.S. metros, our research generates four key findings. First, airports are more likely to be located in larger metros with higher shares of cultural workers and warmer winters. Second, airports add significantly to regional development measured as economic output per capita. Third, the effect of airports on regional development occurs through two channels—their capacity to move both people and cargo, with the former being somewhat more important. Fourth, the impact of airports on regional development varies with their size and scale.

  • 4.
    Holgersson, Thomas
    Jönköping University.
    A Comparative Study of Ten Asymmetry Tests2011In: Journal of Statistics, ISSN 1684-8403, Vol. 18, p. 10-28Article in journal (Refereed)
    Abstract [en]

    In this paper, we investigate the properties of some common tests for Asymmetry.The tests are based on Moments, Order Statistics and Empirical CharacteristicFunctions, respectively. These tests have completely different origins, rely ondifferent characterizations of symmetry and have very different size and powerproperties. It is demonstrated that tests based on Empirical CharacteristicFunctions are strongly dependent on the choice of working region and that somepreviously proposed tests may be improved considerably by using Bootstrappedcritical values. It is also concluded that no test is uniformly better than the othersbut that the Empirical Characteristic Function tests have best over-all properties.

  • 5.
    Holgersson, Thomas
    Högskolan i Jönköping.
    A Graphical Technique for Assessing Multivariate Non-normality2006In: Computational statistics (Zeitschrift), ISSN 0943-4062, E-ISSN 1613-9658, Vol. 21, no 1, p. 141-149Article in journal (Refereed)
    Abstract [en]

    In this paper we suggest a simple graphical device for assessing multivariate normality. The method is based on the characteristic that linear combinations of the sample mean and sample covariance matrix are independent if and only if the random variable is normally distributed. We demonstrate the usage of the suggested method and compare it to the classical Q-Q plot by using some multivariate data sets.

  • 6.
    Holgersson, Thomas
    Högskolan i Jönköping.
    A Modified Skewness Measure for Testing Asymmetry2010In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 39, no 2, p. 335-346Article in journal (Refereed)
    Abstract [en]

    Statistical practitioners frequently wish to know whether a variable is symmetrically distributed. There are a number of different tests available but the most commonly used one is perhaps that based on the standardized third central moment, as defined by Pearson and Fisher in the early 1900's. While this traditional skewness measure uniquely determines the symmetry of a variable within the Pearson family, it does not uniquely determine symmetry for a general distribution. In this article, we propose a modified version of the classical skewness test which is easy to conduct and consistent against a wide family of asymmetric distributions.

  • 7.
    Holgersson, Thomas
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    A note on a commonly used ridge regression Monte Carlo design2015In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 44, no 10, p. 2176-2179Article in journal (Refereed)
    Abstract [en]

    Ridge estimators are usually examined through Monte Carlo simulations since their properties are difficult to obtain analytically. In this paper we argue that a simulation design commonly used in the literature will give biased results of Monte Carlo simulations in favour of ridge regression over ordinary least square (OLS) estimators. Specifically, it is argued that the properties of ridge estimators that are functions of pdistinct regressor eigenvalues should not be evaluated through Monte Carlo designs using only two distinct eigenvalues.

  • 8.
    Holgersson, Thomas
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Festschrift in honor of Professor Ghazi Shukur on the occasion of his 60th birthday2015Collection (editor) (Other academic)
  • 9.
    Holgersson, Thomas
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    How to formulate relevant and assessable learning outcomes in statistics2016In: Creative Education, ISSN 2151-4755, E-ISSN 2151-4771, Vol. 7, no 4, p. 669-675Article in journal (Refereed)
    Abstract [en]

    Course syllabuses, outlines or similar academic documents specifying the content of a course will often be a helpful tool both for teachers and students to grasp the content and purpose of a course. In many cases, however, the compilation of such documents is a painstaking process for the educator designing it, and is a task that many teachers will shun. In this paper we propose a fairly simple pedagogical model for designing specific learning outcomes that the students are expected to attain after completion of a course.

  • 10.
    Holgersson, Thomas
    Högskolan i Jönköping.
    Naturvärden i jordbrukslandskapet: en pilotstudie2008Report (Other academic)
  • 11.
    Holgersson, Thomas
    Högskolan i Jönköping.
    Robust Testing for Skewness2006In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 36, no 3, p. 485-498Article in journal (Refereed)
    Abstract [en]

    Statistical analysis frequently involves the problem of assessing distributional properties. This article concerns the problem of testing for skewness of random variables. It is argued that the classical skewness test is not very useful for this purpose, and another approach is suggested that is easy to implement and is also robust to heteroscedasticity. The size, power, and robustness properties of the proposed test is evaluated and compared to the classical skewness test by means of Monte Carlo simulations.

  • 12.
    Holgersson, Thomas
    Högskolan i Jönköing.
    Simulation of Non-normal Auto Correlated Variables2006In: Journal of Modern Applied Statistical Methods, ISSN 1538-9472, Vol. 5, no 2, p. 408-416Article in journal (Refereed)
    Abstract [en]

    All statistical methods rely on assumptions to some extent. Two assumptions frequently met in statistical analyses are those of normal distribution and independence. When examining robustness properties of such assumptions by Monte Carlo simulations it is therefore crucial that the possible effects of autocorrelation and non-normality are not confounded so that their separate effects may be investigated. This article presents a number of non-normal variables with non-confounded autocorrelation, thus allowing the analyst to specify autocorrelation or shape properties while keeping the other effect fixed

  • 13.
    Holgersson, Thomas
    Högskolan i Jönköping.
    Testing for Multivariate Autocorrelation2004In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 31, no 4, p. 379-395Article in journal (Refereed)
    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.

  • 14.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping.
    Hansund, Knut Per
    Swedish Board of Agriculture, Jönköping, Sweden.
    Norell, Bo
    Swedish Board of Agriculture, Jönköping, Sweden.
    Ståhlberg, David
    Swedish Board of Agriculture, Jönköping, Sweden.
    Assessing the environmental qualities of permanent grassland2010In: Grassland in a changing world: 23th General Meeting of the European Grassland Federation Kiel, Germany, August 29th - September 2nd 2010 - Grassland Science in Europe, Volume 15 / [ed] Schnyder H., Hopkins A., Isselstein J., Mecke Druck und verlag , 2010Chapter in book (Other academic)
  • 15.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping.
    Hasund, Knut Per
    Swedish Board of Agriculture.
    Norell, Bo
    Swedish Board of Agriculture.
    Ståhlberg, David
    Swedish Board of Agriculture.
    Assessing the biodiversity qualities of permanent grassland2010Conference paper (Refereed)
  • 16.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping.
    Karlsson, Peter S.
    Högskolan i Jönköping.
    An Investigation and Development of Three Estimators of Inverse Covariance Matrices With Applications to the Mahalanobis Distance2010Report (Other academic)
    Abstract [en]

    This paper treats the problem of estimating the inverse covariance matrix in an   increasing   dimension   context.   Specifically,   three   ridge-type   estimators   are considered,  of  which  two  new  are  proposed  by  the  authors  and  one  has  been considered previously. Risk functions for deciding an appropriate value of the ridge coefficient  are  developed  and  the  finite  sample  properties  of  the  estimators  are investigated   in   a   Monte   Carlo   simulation.   Moreover,   risk   functions   for   the Mahalanobis distance are derived which, in turn, leads to three new estimators which has not been considered previously.

  • 17. Holgersson, Thomas
    et al.
    Karlsson, Peter S.
    Jönköping International Business School, Sweden.
    Model Based vs. Model Independent Tests for Cross-correlation2010In: Journal of Modern Applied Statistical Methods, ISSN 1538-9472, Vol. 9, no 1, p. 75-89Article in journal (Refereed)
    Abstract [en]

    This article discusses the issue of whether cross correlation should be tested by model dependent or model independent methods. Several different tests are proposed and their main properties are investigated analytically and with simulations. It is argued that model independent tests should be used in applied work.

  • 18.
    Holgersson, Thomas
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Karlsson, Peter S.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Three estimators of the Mahalanobis distance in high-dimensional data2012In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, no 12, p. 2713-2720Article in journal (Refereed)
    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.

  • 19.
    Holgersson, Thomas
    et al.
    Jönköping University.
    Karlsson, Peter S.
    Jönköping University.
    Mansoor, Rashid
    Jönköping University.
    Estimating mean-standard deviation ratios of financial data2012In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, no 3, p. 657-671Article in journal (Refereed)
    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.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Karlsson, Peter S.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Stephan, Andreas
    Linnaeus University, School of Business and Economics, Department of Management Accounting and Logistics.
    A risk perspective of estimating portfolio weights of the Global Minimum Variance portfolio2016In: Presented at Statistischen Woche 2016, Augsburg, Germany, September 13-16, 2016, 2016Conference paper (Other academic)
    Abstract [en]

    The problem of how to maximize the return on a given portfolio of assets within the theory of Markowitz has been given considerable attention in the literature and improvements of standard methods continues to progress. Recent developments, often based on Stein estimators or other regularized estimators, usually focus on settings when the numbers of assets (say p) is close to the number of observations (n) since this is the scenario met in most real applications. Before any specific method is applied investors would want to know the basic properties and the relative performance of them. The performance of any estimation method, however, depends on which quality criterea of judgement is being used. Proposed methods may be optimal with respect to precision of the parameters involved in the portfolio procedure, on the proximity between estimated vs true global minimum variance portfolio (GMVP) weights, on the out-of-sample performance etc. Moreover, regularized estimators are often associated with very complicated or even unknown sampling distributions, which in turn complicate statistical inference drastically. The extent to which a method allows for statistical inference therefore also becomes an important matter when judging the properties of a data driven GMVP estimator. In this paper we give an in-depth discussion of risk critereas and their impact on GMVP optimization. A Monte Carlo simulation investigating the properties of some common estimators, including a new one proposed by the authors, with respect to several quality critereas is included to compare and contrast recent proposals. An empirical study is also included using Stockholm stock exchange data. 

  • 21.
    Holgersson, Thomas
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Karlsson, Peter S.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Stephan, Andreas
    Jönköping University, Sweden.
    A risk perspective of estimating portfolio weights of the global minimum-variance portfolio2019In: AStA Advances in Statistical Analysis, ISSN 1863-8171, E-ISSN 1863-818X, p. 1-22Article in journal (Refereed)
    Abstract [en]

    The problem of how to determine portfolio weights so that the variance of portfolio returns is minimized has been given considerable attention in the literature, and several methods have been proposed. Some properties of these estimators, however, remain unknown, and many of their relative strengths and weaknesses are therefore difficult to assess for users. This paper contributes to the field by comparing and contrasting the risk functions used to derive efficient portfolio weight estimators. It is argued that risk functions commonly used to derive and evaluate estimators may be inadequate and that alternative quality criteria should be considered instead. The theoretical discussions are supported by a Monte Carlo simulation and two empirical applications where particular focus is set on cases where the number of assets (p) is close to the number of observations (n).

  • 22.
    Holgersson, Thomas
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    Kekezi, Orsa
    Jönköping University.
    Towards a multivariate innovation index2018In: Economics of Innovation and New Technology, ISSN 1043-8599, E-ISSN 1476-8364, no 3, p. 254-272Article in journal (Refereed)
    Abstract [en]

    This paper argues that traditional measures of innovation as a univariate phenomenon may not be dynamic enough to adequately describe the complex nature of innovation. Consequently, the purpose is to develop a multidimensional index of innovation that is able to reflect innovation enablers and outputs. The index may then be used (i) to assess and quantify temporal changes of innovation, (ii) to describe regional differences and similarities of innovation, and (iii) serve as exogenous variables to analyze the importance of innovation for other economic phenomena. Our index is defined in a four-dimensional space of orthogonal axes. An empirical case study is used for demonstration of the index, where 44 variables are collected for all municipalities in Sweden. The index spanning the four-dimensional innovation comprises size, accessibility, firm performance, and agglomeration. The proposed index offers a new way of defining and analyzing innovation and should have a wide range of important applications in a world where innovation is receiving a great deal of recognition.

  • 23.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping.
    Lindström, Fredrik
    Göteborgs universitet.
    A Comparison of Conditioned Versus Unconditioned Forecasts of the VAR(1) Process2005In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 34, no 2, p. 415-427Article in journal (Refereed)
    Abstract [en]

    The properties of a forecast usually depend upon whether or not the forecast is conditioned on the final period observation. In the case of unconditioned forecasts, it is well known that the point predictions are unbiased. If, on the other hand, the forecast is conditional, then the forecast may be biased. Existing analytical results in literature are insufficient for describing the properties of the conditioned forecast properly, particularly in multivariate models. This article examines some finite sample properties of conditioned forecasts of the VAR(1) process by means of Monte Carlo experiments. We use a number of parameter settings for the VAR(1) process to demonstrate that the forecast bias of the conditioned forecast may be considerable. Hence, unless the analyst has a clear idea of whether the conditioned or unconditioned forecast is relevant for the time series being analyzed, statistical inferences may be seriously erratic.

  • 24.
    Holgersson, Thomas
    et al.
    Jönköping University.
    Mansoor, Rashid
    Jönköping University.
    Assessing Normality of High-Dimensional Data2013In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 42, no 2, p. 360-369Article in journal (Refereed)
    Abstract [en]

    The assumption of normality is crucial in many multivariate inference methods and may be even more important when the dimension of data is proportional to the sample size. It is therefore necessary that tests for multivariate non normality remain well behaved in such settings. In this article, we examine the properties of three common moment-based tests for non normality under increasing dimension asymptotics (IDA). It is demonstrated through Monte Carlo simulations that one of the tests is inconsistent under IDA and that one of them stands out as uniformly superior to the other two.

  • 25.
    Holgersson, Thomas
    et al.
    Jönköping University.
    Mansoor, Rashid
    Jönköping University.
    Testing for Autocorrelation in High-dimensional Data2012Report (Other academic)
  • 26.
    Holgersson, Thomas
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    Månsson, Kristofer
    University of Gothenburg.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    Testing for Panel Unit Roots under General Cross-Sectional Dependence2016In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 45, no 5, p. 1785-1801Article in journal (Refereed)
    Abstract [en]

    In this paper we generalize four tests of multivariate linear hypothesis to panel data unit root testing. The test statistics are invariant to certain linear transformations of data and therefore simulated critical values may conveniently be used. It is demonstrated that all four tests remains well behaved in cases of where there are heterogeneous alternatives and cross-correlations between marginal variables. A Monte Carlo simulation is included to compare and contrast the tests with two well-established ones.

  • 27.
    Holgersson, Thomas
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    Nordström, Louise
    Jönköping University.
    Öner, Özge
    Jönköping University.
    Dummy Variables vs. Category-wise Models2014In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 41, no 2, p. 233-241Article in journal (Refereed)
    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.

  • 28.
    Holgersson, Thomas
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping Int Business Sch.
    Norman, T.
    Jönköping Int Business Sch.
    Tavassoli, S.
    Blekinge Institute of Technology.
    In the quest for economic significance: assessing variable importance through mean value decomposition2014In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 21, no 8, p. 545-549Article in journal (Refereed)
    Abstract [en]

    Economic significance is frequently assessed through statistical hypothesis testing, which however, does not always correspond to the implicit economical questions being addressed. In this article we propose using mean value decomposition to assess economic significance. Unlike most previously suggested methods the proposed one is intuitive and simple to conduct. The technique is demonstrated and contrasted with hypothesis tests by an empirical example involving the income of Mexican children, which shows that the two inference approaches provide different and supplementary pieces of information.

  • 29.
    Holgersson, Thomas
    et al.
    Göteborg University.
    Shukur, Ghazi
    Göteborg University.
    Some Aspects of Non-Normality Tests in Systems of Regressions Equations2001In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 30, no 2, p. 291-310Article in journal (Refereed)
    Abstract [en]

    In this paper, a short background of the Jarque and McKenzie (JM) test for non-normality is given, and the small sample properties of the test is examined in view of robustness, size and power. The investigation has been performed using Monte Carlo simulations where factors like, e.g., the number of equations, nominal sizes, degrees of freedom, have been varied.

    Generally, the JM test has shown to have good power properties. The estimated size due to the asymptotic distribution is not very encouraging though. The slow rate of convergence to its asymptotic distribution suggests that empirical critical values should be used in small samples.

    In addition, the experiment shows that the properties of the JM test may be disastrous when the disturbances are autocorrelated. Moreover, the simulations show that the distribution of the regressors may also have a substantial impact on the test, and that homogenised OLS residuals should be used when testing for non-normality in small samples.

  • 30.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping.
    Shukur, Ghazi
    Högskolan i Jönköping.
    Testing for Multivariate Heteroscedasticity2004In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 74, no 12, p. 879-896Article in journal (Refereed)
    Abstract [en]

    In this article, we propose a testing technique for multivariate heteroscedasticity, which is expressed as a test of linear restrictions in a multivariate regression model. Four test statistics with known asymptotical null distributions are suggested, namely the Wald, Lagrange multiplier (LM), likelihood ratio (LR) and the multivariate Rao F-test. The critical values for the statistics are determined by their asymptotic null distributions, but bootstrapped critical values are also used. The size, power and robustness of the tests are examined in a Monte Carlo experiment. Our main finding is that all the tests limit their nominal sizes asymptotically, but some of them have superior small sample properties. These are the F, LM and bootstrapped versions of Wald and LR tests.

  • 31.
    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.2016In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, no 8, p. 1564-1565Article in journal (Refereed)
  • 32.
    Lindh, Jörgen
    et al.
    Högskolan i Jönköping.
    Holgersson, Thomas
    Högskolan i Jönköping.
    Does lego training stimulate pupils’ ability to solve logical problems?2006In: The Hawaii International Conference on Statistics, Mathematics and Related Fields, 2006Conference paper (Refereed)
  • 33.
    Lindh, Jörgen
    et al.
    Högskolan i Jönköping.
    Holgersson, Thomas
    Högskolan i Jönköping.
    Does lego training stimulate pupils' ability to solve logical problems?2006In: Computers and education, ISSN 0360-1315, E-ISSN 1873-782X, Vol. 49, no 4, p. 1097-1111Article in journal (Refereed)
    Abstract [en]

    The purpose of this study is to investigate the effect of a one-year regular robotic toys (lego) training on school pupils’ performance. The underlying pedagogical perspective is the constructionist theory, where the main idea is that knowledge is constructed in the mind of the pupil by active learning.

    The investigation has been made in two steps. The first step was before the treatment and the second after treatment. For both cases we have constructed and included control groups. The data was gathered from different pupils from two different age categories, from different classes, from different schools, and finally from different places in Sweden. We have investigated whether the approach of involving the lego training in the schools activities might lead to improving the adoption process and that the pupils would perform better in mathematics and technique. Our null hypothesis states that the lego robots do not have a positive or negative effect on the pupils’ ability to solve mathematical and logical problems. A one-way ANOVA test leads to acceptance of the null hypothesis. However, when ANOVA test was performed on sub groups of pupils, the null hypothesis was rejected in some cases. This indicates that lego training may be useful for some groups of students. Furthermore, a hypothesis test regarding certain correlation measures was conducted, supporting this theory. In general, the statistical analysis suggest that there is no obvious over-all effect of lego, though there are significant positive effects of lego for sub groups of pupils. In all, we find the results promising enough to suggest a larger experiment to be performed.

    The pupils have different learning styles in their approach to LEGO training. The role of the teacher, as a mediator of knowledge and skills, was crucial for coping with problems related to this kind of technology. The teacher must be able to support the pupils and to make them understand the LEGO Dacta material on a deeper level.

  • 34.
    Lindström, Fredrik
    et al.
    Försäkringskassan.
    Holgersson, Thomas
    Högskolan i Jönköping.
    Forecast mean squared error reductionin the VAR(1) process2009In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 36, no 12, p. 1369-1384Article in journal (Refereed)
    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.

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