المؤلفون: Karlheinz Gröchenig, Georg Zimmermann

المصدر: Journal of Function Spaces and Applications, Vol 2, Iss 1, Pp 25-53 (2004)

مصطلحات موضوعية: Mathematics, QA1-939

الوصف: We characterize several classes of test functions, among them Björck's ultra-rapidly decaying test functions and the Gelfand-Shilov spaces of type S, in terms of the decay of their short-time Fourier transform and in terms of their Gabor coefficients.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/0972-6802Test

الوصول الحر: https://doaj.org/article/af8ec0528b1c412383975289b67bffbfTest

المؤلفون: Arne C. Bathke, Werner Brannath, Edgar Brunner, Martin Happ, Georg Zimmermann

المصدر: The American Statistician. 76:124-130

مصطلحات موضوعية: Statistics and Probability, Kruskal–Wallis one-way analysis of variance, General Mathematics, Rank (computer programming), Nonparametric statistics, 01 natural sciences, Ranking (information retrieval), 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Nonparametric inference, Statistics, 030221 ophthalmology & optometry, 0101 mathematics, Statistics, Probability and Uncertainty, Mathematics

الوصف: Rank-based methods are frequently used in the life sciences, and in the empirical sciences in general. Among the best-known examples of nonparametric rank-based tests are the Wilcoxon-Mann-Whitney ...

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::257451f82b623e1cf075d14bf09316c2Test
https://doi.org/10.1080/00031305.2021.1972836Test

المؤلفون: Frank Konietschke, Cong Cao, Asanka Gunawardana, Georg Zimmermann

المصدر: Statistics in Medicine. 40:4732-4749

مصطلحات موضوعية: ANCOVA, Statistics and Probability, Analysis of covariance, Heteroscedasticity, Models, Statistical, Epidemiology, Variance (accounting), Approximate inference, Research Design, Sample size determination, Sample Size, Homoscedasticity, Covariate, Statistics, Humans, Computer Simulation, Box-type approximation, ANOVA-type statistic, experimental designs, 600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit, Mathematics, Statistical hypothesis testing

الوصف: Adjusting for baseline values and covariates is a recurrent statistical problem in medical science. In particular, variance heteroscedasticity is non-negligible in experimental designs and ignoring it might result in false conclusions. Approximate inference methods are developed to test null hypotheses formulated in terms of adjusted treatment effects and regression parameters in general analysis of covariance designs with arbitrary numbers of factors. Variance homoscedasticity is not assumed. The distributions of the test statistics are approximated using Box-type approximation methods. Extensive simulation studies show that the procedures are particularly suitable when sample sizes are rather small. A real data set illustrates the application of the methods.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1299f76ebba7e0ddb26eeda1b8cfd1cbTest
https://doi.org/10.1002/sim.9092Test

المؤلفون: Georg Zimmermann, Tobias Kiesslich, Andreas Traweger, Marlena Beyreis

المصدر: Scientometrics. 126:1249-1269

مصطلحات موضوعية: 0303 health sciences, Gini coefficient, Impact factor, Inequality, media_common.quotation_subject, General Social Sciences, 010501 environmental sciences, Library and Information Sciences, 01 natural sciences, Computer Science Applications, Journal ranking, 03 medical and health sciences, Ranking, Skewness, Citation distribution, Citation, 030304 developmental biology, 0105 earth and related environmental sciences, Demography, media_common, Mathematics

الوصف: Skewed citation distribution is a major limitation of the Journal Impact Factor (JIF) representing an outlier-sensitive mean citation value per journal The present study focuses primarily on this phenomenon in the medical literature by investigating a total of n = 982 journals from two medical categories of the Journal Citation Report (JCR). In addition, the three highest-ranking journals from each JCR category were included in order to extend the analyses to non-medical journals. For the journals in these cohorts, the citation data (2018) of articles published in 2016 and 2017 classified as citable items (CI) were analysed using various descriptive approaches including e.g. the skewness, the Gini coefficient, and, the percentage of CI contributing 50% or 90% of the journal’s citations. All of these measures clearly indicated an unequal, skewed distribution with highly-cited articles as outliers. The %CI contributing 50% or 90% of the journal’s citations was in agreement with previously published studies with median values of 13–18% CI or 44–60% CI generating 50 or 90% of the journal’s citations, respectively. Replacing the mean citation values (corresponding to the JIF) with the median to represent the central tendency of the citation distributions resulted in markedly lower numerical values ranging from − 30 to − 50%. Up to 39% of journals showed a median citation number of zero in one medical journal category. For the two medical cohorts, median-based journal ranking was similar to mean-based ranking although the number of possible rank positions was reduced to 13. Correlation of mean citations with the measures of citation inequality indicated that the unequal distribution of citations per journal is more prominent and, thus, relevant for journals with lower citation rates. By using various indicators in parallel and the hitherto probably largest journal sample, the present study provides comprehensive up-to-date results on the prevalence, extent and consequences of citation inequality across medical and all-category journals listed in the JCR.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::03899ebaf84f50c7b164cbfb0056b350Test
https://doi.org/10.1007/s11192-020-03812-yTest

المؤلفون: Arne C. Bathke, Georg Zimmermann, Martin Happ, Edgar Brunner

المساهمون: FWF

المصدر: Journal of Statistical Software, Vol 95, Iss 1, Pp 1-22 (2020)
Journal of Statistical Software; Vol 95 (2020); 1-22

مصطلحات موضوعية: Statistics and Probability, Computer science, Statistics, Nonparametric statistics, 01 natural sciences, pseudo-ranks, Mathematics, Mathematical statistics, HA1-4737, Interpretation (model theory), nonparametric statistics, 010104 statistics & probability, Resampling, Independent samples, ranks, R, 0101 mathematics, Statistics, Probability and Uncertainty, Algorithm, Software

الوصف: Many popular nonparametric inferential methods are based on ranks. Among the most commonly used and most famous tests are for example the Wilcoxon-Mann-Whitney test for two independent samples, and the Kruskal-Wallis test for multiple independent groups. However, recently, it has become clear that the use of ranks may lead to paradoxical results in case of more than two groups. Luckily, these problems can be avoided simply by using pseudo-ranks instead of ranks. These pseudo-ranks, however, suffer from being (a) at first less intuitive and not as straightforward in their interpretation, (b) computationally much more expensive to calculate. The computational cost has been prohibitive, for example, for large-scale simulative evaluations or application of resampling-based pseudorank procedures. In this paper, we provide different algorithms to calculate pseudo-ranks efficiently in order to solve problem (b) and thus render it possible to overcome the current limitations of procedures based on pseudo-ranks.

وصف الملف: PB

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a23c1c44ad3ee39ccf59f7917ed42e9Test
https://doi.org/10.18637/jss.v095.c01Test

المؤلفون: Georg Zimmermann

المصدر: Springer Proceedings in Mathematics & Statistics ISBN: 9783030573058

مصطلحات موضوعية: Analysis of covariance, media_common.quotation_subject, Statistics, Covariate, Nonparametric statistics, Statistics::Methodology, Covariance, Additive model, Outcome (probability), Normality, Mathematics, Type I and type II errors, media_common

الوصف: The classical parametric analysis of covariance (ANCOVA) is frequently used when comparing an ordinal outcome variable between two groups, while adjusting for a continuous covariate. However, the normality assumption might be crucial and assuming an underlying additive model might be questionable. Therefore, in the present manuscript, we consider the outcome as truly ordinal and dichotomize the covariate by a median split, in order to transform the testing problem to a nonparametric factorial setting. We propose using either a permutation-based Anderson–Darling type approach in conjunction with the nonparametric combination method or the pseudo-rank version of a nonparametric ANOVA-type test. The results of our extensive simulation study show that both methods maintain the type I error level well, but that the ANOVA-type approach is superior in terms of power for location-shift alternatives. We also discuss some further aspects, which should be taken into account when deciding for the one or the other method. The application of both approaches is illustrated by the analysis of real-life data from a randomized clinical trial with stroke patients.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::7a6dc9b6e26c2f698d55fd10fb5a6f33Test
https://doi.org/10.1007/978-3-030-57306-5_48Test

المؤلفون: Georg Zimmermann, Markus Pauly, Arne C. Bathke

المصدر: Journal of Multivariate Analysis. 177:104594

مصطلحات موضوعية: Statistics and Probability, Analysis of covariance, Numerical Analysis, Heteroscedasticity, Covariance matrix, media_common.quotation_subject, 020206 networking & telecommunications, 02 engineering and technology, Covariance, 01 natural sciences, 010104 statistics & probability, Homoscedasticity, Statistics, 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics, Statistics, Probability and Uncertainty, Normality, Mathematics, Type I and type II errors, Parametric statistics, media_common

الوصف: In applied research, it is often sensible to account for one or several covariates when testing for differences between multivariate means of several groups. However, the “classical” parametric multivariate analysis of covariance (MANCOVA) tests (e.g., Wilks’ Lambda) are based on quite restrictive assumptions (homoscedasticity and normality of the errors), which might be difficult to justify. Furthermore, existing potential remedies (e.g., heteroskedasticity-robust approaches) become inappropriate in cases where the covariance matrices are singular or close to singular. Nevertheless, such scenarios are frequently encountered in the life sciences and other fields, when, for example, in the context of standardized assessments, a summary performance measure as well as its corresponding subscales are analyzed. Moreover, computational issues may also lead to singular covariance structures. In the present manuscript, we consider a general MANCOVA model, allowing for potentially heteroskedastic and even singular covariance matrices as well as non-normal errors. We combine heteroskedasticity-consistent covariance matrix estimation methods with our proposed modified MANCOVA ANOVA-type statistic (MANCATS) and apply two different bootstrap approaches. We provide the proofs of the asymptotic validity of the respective testing procedures as well as the results from an extensive simulation study, which indicate that especially the parametric bootstrap version of the MANCATS outperforms its competitors in most small-sample scenarios, both in terms of type I error rates and power. These considerations are further illustrated and substantiated by examining real-life data from standardized achievement tests. Yet, for large sample sizes, Wald-type approaches are an attractive alternative option. Moreover, the choice between Wald-type and MANCATS-based tests might depend on the particular setting (e.g., the covariance structure, or the alternative under consideration).

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::89cd0a242de08cb71f26c43006aa9472Test
https://doi.org/10.1016/j.jmva.2020.104594Test

المؤلفون: S.B. Weineck, Georg Zimmermann, Tobias Kiesslich, D. Koelblinger

المصدر: PLoS ONE, Vol 14, Iss 11, p e0225360 (2019)
PLoS ONE

مصطلحات موضوعية: 0301 basic medicine, Research Facilities, Science, Libraries, Social Sciences, Linear Regression Analysis, Bibliometrics, Research and Analysis Methods, Information Centers, 03 medical and health sciences, Mathematical and Statistical Techniques, 0302 clinical medicine, Sociology, Advertising, Citation analysis, Librarians, Humans, Statistical Methods, Association (psychology), Scientific Publishing, Marketing, Multidisciplinary, Actuarial science, Arithmetic, Impact factor, Statistics, Records, Research Assessment, Databases, Bibliographic, Communications, Professions, 030104 developmental biology, Physical Sciences, People and Places, Citation Analysis, 030221 ophthalmology & optometry, Regression Analysis, Medicine, Population Groupings, Journal Impact Factor, Periodicals as Topic, Scientific publishing, Citation, Psychology, Mathematics, Research Article

الوصف: Analyses of the Journal Impact Factor (JIF) have grown to be a major topic in scientometric literature. Despite widespread and justified critique concerning the JIF and its application, the size of a journal as a predictor for its longitudinal variability–or stability–on a long-term level has not yet comprehensively been analyzed. This study aims to provide robust evidence for an association between JIF variability and the size of journals, expressed by the number of published articles (citable items). For this purpose, the complete set of journals included in the Incite Journal Citation Reports (JCR) with an JIF in the 2017 JCR edition (n = 8750) were analyzed for the association between journal size and longitudinal JIF dynamics. Our results, based on n = 4792 journals with a complete JIF data set over the timespan of 12 annual JIF changes show that larger journals publishing more citable items experience smaller annual changes of the JIF than smaller journals, yet with this association being reversed for journals with a very large number of total cites. Consequently and in accordance with the genuine intention of the JIF to serve as a basis for decisions on journal subscriptions, evaluation of current changes of the JIF have to be accompanied by consideration of the journal’s size in order to be accurate and sensible.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1aa5aee831a94e7b4cde73704b78fc7Test
https://doi.org/10.1371/journal.pone.0225360Test

المؤلفون: Georg Zimmermann, Marco Artavia, Harald Grethe

المصدر: Economic Modelling. 45:155-168

مصطلحات موضوعية: 630 Landwirtschaft und verwandte Bereiche, Mathematical optimization, Economics and Econometrics, Gaussian Quadratures, Covariance matrix, Gaussian, Monte Carlo method, Stochastic modeling, Outcome (probability), Commodity markets, symbols.namesake, Joint probability distribution, Sampling methods, symbols, ddc:630, Applied mathematics, Economic model, Rotation (mathematics), Monte Carlo, Mathematics, Cholesky decomposition

الوصف: Recently, stochastic applications of large-scale applied simulation models of agricultural markets have become more frequent. However, stochastic modeling with large market models comes with high computational and management costs for data storage, analysis and manipulation. Gaussian Quadratures (GQ), are efficient sampling methods requiring few points to approximate the central moments of the joint probability distribution of stochastic variables and therefore reduce computational costs. For symmetric regions of integration, the vertices of Stroud's n-octahedron (Stroud, 1957) are GQ formulas of degree 3 with a minimal number of points which can make the stochastic modeling with large economic models manageable. However, we have the conjecture that rotations of Stroud's n-octahedron have an effect on the accuracy of approximation of model results; thus, we test eight different rotations using the European Simulation Model (ESIM). It was found that the 45° rotation yields higher accuracy than the 0° rotation. With the 45° rotation and in models with large regions or variables which strongly determine the outcome of model results such as soft wheat in ESIM, the arrangement of the stochastic variables (A1 or A2) in the covariance matrix or the selected method to introduce correlation (via the Cholesky decomposition –C– or via the diagonalization method –D–) may have a significant effect on the accuracy of the quadratures. With the 45° rotation and with markets where the effect of the different regions or variables on model outcomes are more homogenous as in the case of rapeseed in ESIM, the selection of the arrangements A1 or A2 and the method of introducing correlation C or D may not have a significant effect on the accuracy of the quadratures.

وصف الملف: application/pdf

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d446a8659dc9409fcfeb3705ad07fe7bTest

المؤلفون: Georg Zimmermann

المصدر: From Basic Survival Analytic Theory to a Non-Standard Application ISBN: 9783658177188

مصطلحات موضوعية: Survival data, Statistics, Parametric model, Regression analysis, Factor regression model, Mathematics, Weibull distribution

الوصف: In this chapter, we, at first, give a short explanation why regression models are needed for many different types of survival data. Then, we introduce two very popular classes of survival analytic regression models and discuss the relationship between them. When examining the epilepsy dataset, we repeatedly use a particular parametric model called the Weibull model, which is therefore defined in this chapter.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::ce7544f1e608b347676fa58771e8115dTest
https://doi.org/10.1007/978-3-658-17719-5_3Test