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Subject
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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 1,251 - 1,260 of 6,289
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Modelling and forecasting noisy realized volatility
Asai, Manabu; McAleer, Michael; Medeiros, Marcelo C. - In: Computational Statistics & Data Analysis 56 (2012) 1, pp. 217-230
Several methods have recently been proposed in the ultra-high frequency financial literature to remove the effects of microstructure noise and to obtain consistent estimates of the integrated volatility (IV) as a measure of ex post daily volatility. Even bias-corrected and consistent realized...
Persistent link: https://www.econbiz.de/10009274854
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Robust joint modeling of mean and dispersion through trimming
Neykov, N.M.; Filzmoser, P.; Neytchev, P.N. - In: Computational Statistics & Data Analysis 56 (2012) 1, pp. 34-48
The Maximum Likelihood Estimator (MLE) and Extended Quasi-Likelihood (EQL) estimator have commonly been used to estimate the unknown parameters within the joint modeling of mean and dispersion framework. However, these estimators can be very sensitive to outliers in the data. In order to...
Persistent link: https://www.econbiz.de/10009274855
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Multivariate mixture modeling using skew-normal independent distributions
Cabral, Celso Rômulo Barbosa; Lachos, Víctor Hugo; … - In: Computational Statistics & Data Analysis 56 (2012) 1, pp. 126-142
In this paper we consider a flexible class of models, with elements that are finite mixtures of multivariate skew-normal independent distributions. A general EM-type algorithm is employed for iteratively computing parameter estimates and this is discussed with emphasis on finite mixtures of...
Persistent link: https://www.econbiz.de/10009274856
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On generalised asymmetric stochastic volatility models
Tsiotas, Georgios - In: Computational Statistics & Data Analysis 56 (2012) 1, pp. 151-172
Stochastic volatility (SV) models have been considered as a real alternative to time-varying volatility of the ARCH family. Existing asymmetric SV (ASV) models treat volatility asymmetry via the leverage effect hypothesis. Generalised ASV models that take account of both volatility asymmetry and...
Persistent link: https://www.econbiz.de/10009274858
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A periodic Levinson-Durbin algorithm for entropy maximization
Boshnakov, Georgi N.; Lambert-Lacroix, Sophie - In: Computational Statistics & Data Analysis 56 (2012) 1, pp. 15-24
A recursive algorithm is presented for the computation of the first-order and second-order derivatives of the entropy of a periodic autoregressive process with respect to the autocovariances. It is an extension of the periodic Levinson-Durbin algorithm. The algorithm has been developed for use...
Persistent link: https://www.econbiz.de/10009274859
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Constructing a Pareto front approximation for decision making
Hartikainen, Markus; Miettinen, Kaisa; Wiecek, Margaret - In: Computational Statistics 73 (2011) 2, pp. 209-234
An approach to constructing a Pareto front approximation to computationally expensive multiobjective optimization problems is developed. The approximation is constructed as a sub-complex of a Delaunay triangulation of a finite set of Pareto optimal outcomes to the problem. The approach is based...
Persistent link: https://www.econbiz.de/10010759591
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Maximizing upgrading and downgrading margins for ordinal regression
Carrizosa, Emilio; Martin-Barragan, Belen - In: Computational Statistics 74 (2011) 3, pp. 381-407
In ordinal regression, a score function and threshold values are sought to classify a set of objects into a set of ranked classes. Classifying an individual in a class with higher (respectively lower) rank than its actual rank is called an upgrading (respectively downgrading) error. Since...
Persistent link: https://www.econbiz.de/10010759603
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Extensions to online delay management on a single train line: new bounds for delay minimization and profit maximization
Krumke, Sven; Thielen, Clemens; Zeck, Christiane - In: Computational Statistics 74 (2011) 1, pp. 53-75
We present extensions to the Online Delay Management Problem on a Single Train Line. While a train travels along the line, it learns at each station how many of the passengers wanting to board the train have a delay of δ. If the train does not wait for them, they get delayed even more since...
Persistent link: https://www.econbiz.de/10010847515
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Risk averse asymptotics in a Black–Scholes market on a finite time horizon
Grandits, Peter; Thonhauser, Stefan - In: Computational Statistics 74 (2011) 1, pp. 21-40
We consider the optimal investment and consumption problem in a Black–Scholes market, if the target functional is given by expected discounted utility of consumption plus expected discounted utility of terminal wealth. We investigate the behaviour of the optimal strategies, if the relative...
Persistent link: https://www.econbiz.de/10010847534
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On generalized balanced optimization problems
Turner, Lara; Punnen, Abraham; Aneja, Yash; Hamacher, Horst - In: Computational Statistics 73 (2011) 1, pp. 19-27
In the generalized balanced optimization problem (GBaOP) the objective value $${\max_{e \in S}{|c(e)-k\max(S)|}}$$ is minimized over all feasible subsets S of E = {1, . . . , m}. We show that the algorithm proposed in Punnen and Aneja (Oper Res Lett 32:27–30, 2004 ) can be modified to ensure...
Persistent link: https://www.econbiz.de/10010847567
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