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EM algorithm 47 Bootstrap 37 Variable selection 36 Model selection 35 Markov chain Monte Carlo 34 Maximum likelihood 25 Robustness 24 Simulation 23 Classification 22 Dynamic programming 22 Bayesian inference 19 Markov decision processes 19 Confidence interval 18 Quantile regression 18 Clustering 17 Consistency 17 Dimension reduction 17 MCMC 16 Survival analysis 15 Functional data 14 Functional data analysis 14 Generalized linear models 14 Importance sampling 14 Longitudinal data 14 Maximum likelihood estimation 14 Nonparametric regression 14 Optimal control 14 Robust estimation 14 Core 13 Linear programming 13 Logistic regression 13 Monte Carlo simulation 13 Density estimation 12 Lasso 12 Optimization 12 Random effects 12 Regularization 12 Shapley value 12 Cluster analysis 11 Gibbs sampling 11
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Undetermined 6,248 Free 5
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Article 6,272 Book / Working Paper 17
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Collection of articles of several authors 4 Sammelwerk 4 Aufsatzsammlung 2 Handbook 1 Handbuch 1
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Undetermined 6,277 English 12
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Balakrishnan, N. 40 Molenberghs, Geert 22 Tang, Man-Lai 22 Kundu, Debasis 21 Paula, Gilberto A. 16 Trenkler, Gotz 16 Lee, Sik-Yum 15 Cordeiro, Gauss M. 14 Hawkins, Douglas M. 14 Tijs, Stef 14 Tian, Guo-Liang 13 Cribari-Neto, Francisco 12 Nadarajah, Saralees 12 Tutz, Gerhard 12 Borm, Peter 11 Chen, Hubert J. 11 Hubert, Mia 11 Lee, Jae Won 11 Lemonte, Artur J. 11 Ortega, Edwin M.M. 11 Poon, Wai-Yin 11 Priebe, Carey E. 11 Rousseeuw, Peter J. 11 Bentler, Peter M. 10 Dodge, Yadolah 10 Hernández-Lerma, Onésimo 10 Agresti, Alan 9 Brown, Morton B. 9 Cavazos-Cadena, Rolando 9 Croux, Christophe 9 Gerlach, Richard 9 Lesaffre, Emmanuel 9 Liang, Hua 9 Lui, Kung-Jong 9 Shin, Dong Wan 9 Wang, Yong 9 D'Urso, Pierpaolo 8 Ferrari, Silvia L.P. 8 Fraiman, Ricardo 8 Gupta, Ramesh C. 8
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Computational Statistics & Data Analysis 4,738 Computational Statistics 1,534 Springer handbooks of computational statistics 3 Computational Statistics and Data Analysis 2 Computational Statistics and Data Analysis 143 (2020) 106843 1 Computational Statistics and Data Analysis 56 (2012) 1–14 1 Computational Statistics and Data Analysis, Forthcoming 1 Karabatsos, G. (2022). Approximate Bayesian computation using asymptotically normal point estimates. Computational Statistics, 1-38 1 Springer Handbooks of Computational Statistics 1 https://doi.org/10.1016/j.csda.2019.106843 Previous title "HOW MANY PARAMETERS DOES MY KERNEL DENSITY ESTIMATE HAVE?" 1
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RePEc 6,272 ECONIS (ZBW) 11 USB Cologne (EcoSocSci) 6
Showing 771 - 780 of 6,289
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Efficient power computation for r out of m runs rules schemes
Mehmood, Rashid; Riaz, Muhammad; Does, Ronald - In: Computational Statistics 28 (2013) 2, pp. 667-681
In this article we develop a power computation code in the R language which provides an easy to use tool to researchers in designing Shewhart control charts. It enables researchers to use different existing and newly introduced sensitizing rules and runs rules schemes designed for Shewhart-type...
Persistent link: https://www.econbiz.de/10010998508
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Generalized joint Procrustes analysis
Adachi, Kohei - In: Computational Statistics 28 (2013) 6, pp. 2449-2464
In this paper, we propose a generalized version of Adachi’s (Psychometrika 74:667–683, <CitationRef CitationID="CR1">2009</CitationRef>) Joint Procrustes Analysis (GJPA), in order to transform the principal component score and loading matrices obtained for multiple data sets of the same size. The transformation is made so that...</citationref>
Persistent link: https://www.econbiz.de/10010998509
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Proposal adaptation in simulated annealing for continuous optimization problems
Solonen, Antti - In: Computational Statistics 28 (2013) 5, pp. 2049-2065
In recent years, adaptive Markov Chain Monte Carlo (MCMC) methods have become a standard tool for Bayesian parameter estimation. In adaptive MCMC, the past iterations are used to tune the proposal distribution of the algorithm. The same adaptation mechanisms can be used in Simulated Annealing...
Persistent link: https://www.econbiz.de/10010998510
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Estimating critical values for testing the i.i.d. in standardized residuals from GARCH models in finite samples
Pérez-Rodríguez, Jorge; Andrada-Félix, Julián - In: Computational Statistics 28 (2013) 2, pp. 701-734
Taking into account that the BDS test—which is used as a misspecification test applied to standardized residuals from the GARCH(1,1) model—is characterized by size distortion and departure from normality in finite samples, this paper obtains the critical values for the finite sample...
Persistent link: https://www.econbiz.de/10010998511
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Nonparametric prediction intervals for progressive Type-II censored order statistics based on <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$k$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>k</mi> </math> </EquationSource> </InlineEquation>-records
Basiri, Elham; Ahmadi, Jafar - In: Computational Statistics 28 (2013) 6, pp. 2825-2848
In this paper, we consider the prediction problem in two-sample case and study the non-parametric predicting future progressively Type-II censored order statistics based on observed <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$k$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>k</mi> </math> </EquationSource> </InlineEquation>-records from the same distribution. Also, prediction intervals for progressively Type-II censored...</equationsource></equationsource></inlineequation>
Persistent link: https://www.econbiz.de/10010998512
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A characterization for truncated cauchy random variables with nonzero skewness parameter
Shirvani, A.; Soltani, A. - In: Computational Statistics 28 (2013) 3, pp. 1011-1016
Soltani and Shirvani (Comput Stat 25:155–161, <CitationRef CitationID="CR5">2010</CitationRef>) provided a characterization and a simulation method for truncated stable random variables when the characteristic exponent <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$\alpha \ne 1 $$</EquationSource> </InlineEquation>, and left the case <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$\alpha =1$$</EquationSource> </InlineEquation> open. The case of <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$\alpha =1$$</EquationSource> </InlineEquation> is treated in this article....</equationsource></inlineequation></equationsource></inlineequation></equationsource></inlineequation></citationref>
Persistent link: https://www.econbiz.de/10010998513
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Goodness-of-fit indices for partial least squares path modeling
Henseler, Jörg; Sarstedt, Marko - In: Computational Statistics 28 (2013) 2, pp. 565-580
This paper discusses a recent development in partial least squares (PLS) path modeling, namely goodness-of-fit indices. In order to illustrate the behavior of the goodness-of-fit index (GoF) and the relative goodness-of-fit index (GoF<Subscript>rel</Subscript>), we estimate PLS path models with simulated data, and...</subscript>
Persistent link: https://www.econbiz.de/10010998514
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Evaluation of confidence intervals for the kappa statistic when the assumption of marginal homogeneity is violated
Parpia, Sameer; Koval, John; Donner, Allan - In: Computational Statistics 28 (2013) 6, pp. 2709-2718
This article studies the robustness of confidence interval construction for the intraclass kappa statistic based on a dichotomous response when the assumption of marginal homogeneity across two raters is violated. Two methods of construction are considered: the goodness-of-fit approach and the...
Persistent link: https://www.econbiz.de/10010998515
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Neighbourhood of spatial areas in the physical and socio-economical context
Młodak, Andrzej - In: Computational Statistics 28 (2013) 6, pp. 2379-2414
In this paper a comparison of two concepts of neighbourhoods of spatial areas—physical and socio-economical—is presented. The former usually concerns their location on an administrative map and a possible community of borders, the latter—a similarity in terms of a composite social or...
Persistent link: https://www.econbiz.de/10010998516
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Ranking ranks: a ranking algorithm for bootstrapping from the empirical copula
Blumentritt, Thomas; Grothe, Oliver - In: Computational Statistics 28 (2013) 2, pp. 455-462
Nonparametric copula models are based on observations whose distributions are generally unknown. Estimation of these copula models is based on pseudo-observations consisting of the ranked data. To determine distributional properties (e.g., the variance) of the models and their estimators,...
Persistent link: https://www.econbiz.de/10010998520
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