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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 941 - 950 of 6,289
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A simple additivity test for conditionally heteroscedastic nonlinear autoregression
Levine, Michael; Li, Jinguang - In: Computational Statistics & Data Analysis 56 (2012) 8, pp. 2421-2429
In this article, we propose a test for the additivity of a nonlinear conditionally heteroscedastic autoregressive model. The test is based on the unequal variance unbalanced design ANOVA scheme. An asymptotic distribution of the test statistic is derived and the test performance in finite...
Persistent link: https://www.econbiz.de/10010871458
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Testing the equality of a large number of normal population means
Park, Junyong; Park, DoHwan - In: Computational Statistics & Data Analysis 56 (2012) 5, pp. 1131-1149
It is challenging to consider the problem of testing the equality of normal population means when the number of populations is large compared to the sample sizes. In ANOVA with the assumption of homogeneous variance, the F-test is known as an exact test. When variances are heterogeneous, due to...
Persistent link: https://www.econbiz.de/10010871462
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Modeling the random effects covariance matrix for generalized linear mixed models
Lee, Keunbaik; Lee, JungBok; Hagan, Joseph; Yoo, Jae Keun - In: Computational Statistics & Data Analysis 56 (2012) 6, pp. 1545-1551
Generalized linear mixed models (GLMMs) are commonly used to analyze longitudinal categorical data. In these models, we typically assume that the random effects covariance matrix is constant across the subject and is restricted because of its high dimensionality and its positive definiteness....
Persistent link: https://www.econbiz.de/10010871465
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Empirical assessment of the Maximum Likelihood Estimator quality in a parametric counting process model for recurrent events
Babykina, Génia; Couallier, Vincent - In: Computational Statistics & Data Analysis 56 (2012) 2, pp. 297-315
A particular parametric model, based on the counting process theory, and aimed at the analysis of recurrent events is explored. The model is built in the context of reliability of repairable systems and is used to analyze failures of water distribution pipes. The proposed model accounts for...
Persistent link: https://www.econbiz.de/10010871466
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Semiparametric regression models with additive nonparametric components and high dimensional parametric components
Du, Pang; Cheng, Guang; Liang, Hua - In: Computational Statistics & Data Analysis 56 (2012) 6, pp. 2006-2017
This paper concerns semiparametric regression models with additive nonparametric components and high dimensional parametric components under sparsity assumptions. To achieve simultaneous model selection for both nonparametric and parametric parts, we introduce a penalty that combines the...
Persistent link: https://www.econbiz.de/10010871469
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Shape restricted nonparametric regression with Bernstein polynomials
Wang, J.; Ghosh, S.K. - In: Computational Statistics & Data Analysis 56 (2012) 9, pp. 2729-2741
The objective of this article is to develop a computationally efficient estimator of the regression function subject to various shape constraints. In particular, nonparametric estimators of monotone and/or convex (concave) regression functions are obtained by using a nested sequence of Bernstein...
Persistent link: https://www.econbiz.de/10010871475
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Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions
Shen, Yuan; Cornford, Dan; Opper, Manfred; Archambeau, … - In: Computational Statistics 27 (2012) 1, pp. 149-176
Persistent link: https://www.econbiz.de/10010847489
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Optimal stopping with random exercise lag
Lempa, Jukka - In: Computational Statistics 75 (2012) 3, pp. 273-286
We study optimal stopping with exponentially distributed exercise lag. We formalize the problem first in a general Markovian setting and derive a set of conditions under which the solution exists. In particular, no semicontinuity assumptions of the payoff function are needed. We analyze also...
Persistent link: https://www.econbiz.de/10010847507
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Flexible scan statistic test to detect disease clusters in hierarchical trees
Prates, Marcos; Assunção, Renato; Costa, Marcelo - In: Computational Statistics 27 (2012) 4, pp. 715-737
This paper presents a flexible scan test statistic to detect disease clusters in data sets represented as a hierarchical tree. The algorithm searches through the branches of the tree and it is able to aggregate leaves located in different branches. The test statistic combines two terms, the...
Persistent link: https://www.econbiz.de/10010847517
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Rayleigh projection depth
Hu, Yonggang; Li, Qiang; Wang, Yong; Wu, Yi - In: Computational Statistics 27 (2012) 3, pp. 523-530
In this paper, a novel projection-based depth based on the Rayleigh quotient, Rayleigh projection depth (RPD), is proposed. Although, the traditional projection depth (PD) has many good properties, it is indeed not practical due to its difficult computation, especially for the high-dimensional...
Persistent link: https://www.econbiz.de/10010847520
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