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 Author:
 Chung, Dongjun; Kim, Hyunjoong
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 113
 ISSN:
 01679473
 Subject:
 data collection; filters; prediction; pruning
 Abstract:
 ... Ensemble pruning deals with the selection of base learners prior to combination in order to improve prediction accuracy and efficiency. In the ensemble literature, it has been pointed out that in order for an ensemble classifier to achieve higher prediction accuracy, it is critical for the ensemble classifier to consist of accurate classifiers which at the same time diverse as much as possible. In ...
 DOI:
 10.1016/j.csda.2014.09.003

http://dx.doi.org/10.1016/j.csda.2014.09.003
 Author:
 Kang, Fangyuan; Sun, Liuquan; Zhao, Xingqiu
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 151167
 ISSN:
 01679473
 Subject:
 models
 Abstract:
 ... In this article, a class of transformed hazards models is proposed for recurrent gap time data, including both the proportional and additive hazards models as special cases. An estimating equationbased inference procedure is developed for the model parameters, and the asymptotic properties of the resulting estimators are established. In addition, a lackoffit test is presented to assess the adeq ...
 DOI:
 10.1016/j.csda.2014.10.005

http://dx.doi.org/10.1016/j.csda.2014.10.005
 Author:
 Mbalawata, Isambi S.; Särkkä, Simo; Vihola, Matti; Haario, Heikki
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 101115
 ISSN:
 01679473
 Subject:
 Bayesian theory; Markov chain; algorithms; variance covariance matrix
 Abstract:
 ... Markov chain Monte Carlo (MCMC) methods are powerful computational tools for analysis of complex statistical problems. However, their computational efficiency is highly dependent on the chosen proposal distribution, which is generally difficult to find. One way to solve this problem is to use adaptive MCMC algorithms which automatically tune the statistics of a proposal distribution during the MCM ...
 DOI:
 10.1016/j.csda.2014.10.006

http://dx.doi.org/10.1016/j.csda.2014.10.006
 Author:
 White, Staci A.; Herbei, Radu
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 168181
 ISSN:
 01679473
 Subject:
 Bayesian theory; differential equation; models; motivation; probability
 Abstract:
 ... Quantifying the discrepancy between two distributions is considered, using the concept of ϕdivergence. The motivation is a Bayesian inference scenario where one is interested in comparing different posterior distributions. Strongly consistent estimators for the ϕdivergence between two posterior distributions are developed. The proposed estimators alleviate known computational difficulties with e ...
 DOI:
 10.1016/j.csda.2014.10.008

http://dx.doi.org/10.1016/j.csda.2014.10.008
 Author:
 Zhang, Jun; Li, Gaorong; Feng, Zhenghui
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 5264
 ISSN:
 01679473
 Subject:
 regression analysis
 Abstract:
 ... This paper studies tools for checking the validity of a parametric regression model, when both response and predictors are unobserved and distorted in a multiplicative fashion by an observed confounding variable. A residual based empirical process test statistic marked by proper functions of the regressors is proposed. We derive asymptotic distribution of the proposed empirical process test statis ...
 DOI:
 10.1016/j.csda.2014.09.018

http://dx.doi.org/10.1016/j.csda.2014.09.018
 Author:
 Bhattacharya, Ritwik; Pradhan, Biswabrata; Dewanji, Anup
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 91100
 ISSN:
 01679473
 Subject:
 Monte Carlo method; Weibull statistics; models; risk
 Abstract:
 ... The decision regarding acceptance or rejection of a lot of products may be considered through variables acceptance sampling plans based on suitable quality characteristics. A variables sampling plan to determine the acceptability of a lot of products based on the lifetime of the products is called reliability acceptance sampling plan (RASP). This work considers the determination of optimum RASP un ...
 DOI:
 10.1016/j.csda.2014.10.002

http://dx.doi.org/10.1016/j.csda.2014.10.002
 Author:
 Kong, Dehan; Bondell, Howard D.; Wu, Yichao
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 236250
 ISSN:
 01679473
 Subject:
 algorithms; models; regression analysis; variance
 Abstract:
 ... In this article, we consider the varying coefficient model, which allows the relationship between the predictors and response to vary across the domain of interest, such as time. In applications, it is possible that certain predictors only affect the response in particular regions and not everywhere. This corresponds to identifying the domain where the varying coefficient is nonzero. Towards this ...
 DOI:
 10.1016/j.csda.2014.10.004

http://dx.doi.org/10.1016/j.csda.2014.10.004
 Author:
 Maronna, Ricardo A.; Yohai, Victor J.
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 262274
 ISSN:
 01679473
 Subject:
 linear models; statistical analysis
 Abstract:
 ... Good robust estimators can be tuned to combine a high breakdown point and a specified asymptotic efficiency at a central model. This happens in regression with MM and τestimators among others. However, the finitesample efficiency of these estimators can be much lower than the asymptotic one. To overcome this drawback, an approach is proposed for parametric models, which is based on a distance b ...
 DOI:
 10.1016/j.csda.2014.10.015

http://dx.doi.org/10.1016/j.csda.2014.10.015
 Author:
 Wang, Bing Xing; Ye, ZhiSheng
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 2636
 ISSN:
 01679473
 Subject:
 Weibull statistics; confidence interval; models; variance
 Abstract:
 ... Record data are commonly seen in everyday life, e.g., concentration of emerging contaminants in environmental studies. Based on record data, this study investigates point estimation and confidence intervals estimation for the Weibull distribution. The uniformly minimum variance unbiased estimator for the Weibull shape is derived. Based on this estimator, a biascorrected estimator for the Weibull ...
 DOI:
 10.1016/j.csda.2014.09.005

http://dx.doi.org/10.1016/j.csda.2014.09.005
 Author:
 Castillo, Joan del; Serra, Isabel
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 116128
 ISSN:
 01679473
 Subject:
 Bayesian theory; models; statistical analysis
 Abstract:
 ... A new methodological approach that enables the use of the maximum likelihood method in the Generalized Pareto Distribution is presented. Thus several models for the same data can be compared under Akaike and Bayesian information criteria. The view is based on a detailed theoretical study of the Generalized Pareto Distribution submodels with compact support. ...
 DOI:
 10.1016/j.csda.2014.10.014

http://dx.doi.org/10.1016/j.csda.2014.10.014
 Author:
 Wang, WanLun
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 223235
 ISSN:
 01679473
 Subject:
 algorithms; data collection; models
 Abstract:
 ... Mixtures of common tfactor analyzers (MCtFA) have emerged as a sound parsimonious modelbased tool for robust modeling of highdimensional data in the presence of fattailed noises and atypical observations. This paper presents a generalization of MCtFA to accommodate missing values as they frequently occur in many scientific researches. Under a missing at random mechanism, a computationally effi ...
 DOI:
 10.1016/j.csda.2014.10.007

http://dx.doi.org/10.1016/j.csda.2014.10.007
 Author:
 Christiansen, Marcus C.; Niemeyer, Andreas; Teigiszerová, Lucia
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 6581
 ISSN:
 01679473
 Subject:
 insurance; longevity; models; mortality
 Abstract:
 ... Mortality data of disabled individuals are studied and parametric modeling approaches for the force of mortality are discussed. Empirical observations show that the duration since disablement has a strong effect on mortality rates. In order to incorporate duration effects, different generalizations of the Lee–Carter model are proposed. For each proposed model, uniqueness properties and fitting tec ...
 DOI:
 10.1016/j.csda.2014.09.017

http://dx.doi.org/10.1016/j.csda.2014.09.017
 Author:
 Hanafi, Mohamed; Ouertani, Samia Samar; Boccard, Julien; Mazerolles, Gérard; Rudaz, Serge
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 129139
 ISSN:
 01679473
 Subject:
 algorithms; models; regression analysis
 Abstract:
 ... The trilinear PLS2 iterative procedure, an algorithm pertaining to the NIPALS framework, is considered. It was previously proposed as a first stage to estimate parameters of the multiway PLS regression method. It is shown that the trilinear PLS2 procedure is convergent. The procedure generates a sequence of parameters (scores and loadings), which can be described as increasing or decreasing two ...
 DOI:
 10.1016/j.csda.2014.10.003

http://dx.doi.org/10.1016/j.csda.2014.10.003
 Author:
 Touloumis, Anestis
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 251261
 ISSN:
 01679473
 Subject:
 colorectal neoplasms; data collection; variance covariance matrix
 Abstract:
 ... Estimating a covariance matrix is an important task in applications where the number of variables is larger than the number of observations. Shrinkage approaches for estimating a highdimensional covariance matrix are often employed to circumvent the limitations of the sample covariance matrix. A new family of nonparametric Steintype shrinkage covariance estimators is proposed whose members are w ...
 DOI:
 10.1016/j.csda.2014.10.018

http://dx.doi.org/10.1016/j.csda.2014.10.018
 Author:
 Diaz, Mireya
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 8290
 ISSN:
 01679473
 Subject:
 disease prevalence; metaanalysis; models; probability
 Abstract:
 ... The bivariate random effects model has been advocated for the metaanalysis of diagnostic accuracy despite scarce information regarding its statistical performance for noncomparative categorical outcomes. Four staggered simulation experiments using a fullfactorial design were conducted to assess such performance over a wide range of scenarios. The number of studies, the number of individuals per ...
 DOI:
 10.1016/j.csda.2014.09.021

http://dx.doi.org/10.1016/j.csda.2014.09.021
 Author:
 De Oliveira, Victor; Kone, Bazoumana
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 3751
 ISSN:
 01679473
 Subject:
 algorithms; chromium; geostatistics; prediction; probability; Switzerland
 Abstract:
 ... Methodology is proposed for the construction of prediction intervals for integrals of Gaussian random fields over bounded regions (called block averages in the geostatistical literature) based on observations at a finite set of sampling locations. Two bootstrap calibration algorithms are proposed, termed indirect and direct, aimed at improving upon plugin prediction intervals in terms of coverage ...
 DOI:
 10.1016/j.csda.2014.09.013

http://dx.doi.org/10.1016/j.csda.2014.09.013
 Author:
 Wang, Naichen; Wang, Lianming; McMahan, Christopher S.
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 140150
 ISSN:
 01679473
 Subject:
 Chlamydia; algorithms; data collection; models; public health; regression analysis; Nebraska
 Abstract:
 ... The Gammafrailty proportional hazards (PH) model is commonly used to analyze correlated survival data. Despite this model’s popularity, the analysis of correlated current status data under the Gammafrailty PH model can prove to be challenging using traditional techniques. Consequently, in this paper we develop a novel expectation–maximization (EM) algorithm under the Gammafrailty PH model to st ...
 DOI:
 10.1016/j.csda.2014.10.013

http://dx.doi.org/10.1016/j.csda.2014.10.013
 Author:
 Hwang, Eunju; Shin, Dong Wan
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 1425
 ISSN:
 01679473
 Subject:
 Monte Carlo method; autocorrelation; models; time series analysis
 Abstract:
 ... For panels of possible crosssectional and serial dependency, stationary bootstrapping is applied to construct unit root tests that are valid regardless of the nuisance parameters of such dependency. The tests are semiparametric in that no model structure is imposed on the serial correlation and the crosssectional correlation. The statistics are Wald tests and tbar type tests based on the OLSE ( ...
 DOI:
 10.1016/j.csda.2014.09.004

http://dx.doi.org/10.1016/j.csda.2014.09.004
 Author:
 Peavoy, Daniel; Franzke, Christian L.E.; Roberts, Gareth O.
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 182199
 ISSN:
 01679473
 Subject:
 Bayesian theory; algorithms; climate models; differential equation; energy conservation
 Abstract:
 ... A systematic Bayesian framework is developed for physics constrained parameter inference of stochastic differential equations (SDE) from partial observations. Physical constraints are derived for stochastic climate models but are applicable for many fluid systems. A condition is derived for global stability of stochastic climate models based on energy conservation. Stochastic climate models are gl ...
 DOI:
 10.1016/j.csda.2014.10.011

http://dx.doi.org/10.1016/j.csda.2014.10.011
 Author:
 Ma, Yingying; Lan, Wei; Wang, Hansheng
 Source:
 Computational statistics & data analysis 2015 v.83 pp. 275286
 ISSN:
 01679473
 Subject:
 advertising; regression analysis
 Abstract:
 ... We consider here the problem of testing the effect of a subset of predictors for a regression model with predictor dimension fixed but ultra high dimensional responses. Because the response dimension is ultra high, the classical method of likelihood ratio test is no longer applicable. To solve the problem, we propose a novel solution, which decomposes the original problem into many testing problem ...
 DOI:
 10.1016/j.csda.2014.09.020

http://dx.doi.org/10.1016/j.csda.2014.09.020