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Computational Statistics & Data Analysis, Volume 59
Volume 59, March 2013
- Ida Hertel, Michael Kohler:

Estimation of the optimal design of a nonlinear parametric regression problem via Monte Carlo experiments. 1-12 - Andrew T. Karl

, Yan Yang, Sharon L. Lohr:
Efficient maximum likelihood estimation of multiple membership linear mixed models, with an application to educational value-added assessments. 13-27 - Kei Hirose, Shohei Tateishi, Sadanori Konishi:

Tuning parameter selection in sparse regression modeling. 28-40 - Yili Hong:

On computing the distribution function for the Poisson binomial distribution. 41-51
- J. Dißmann, Eike C. Brechmann, Claudia Czado

, Dorota Kurowicka:
Selecting and estimating regular vine copulae and application to financial returns. 52-69 - Mayukh Samanta, Alan H. Welsh

:
Bootstrapping for highly unbalanced clustered data. 70-81 - Oleksandr Gromenko, Piotr Kokoszka:

Nonparametric inference in small data sets of spatially indexed curves with application to ionospheric trend determination. 82-94 - Jiajia Zhang, Yingwei Peng, Haifen Li:

A new semiparametric estimation method for accelerated hazards mixture cure model. 95-102 - Jun Zhang

, Yujie Gai, Ping Wu:
Estimation in linear regression models with measurement errors subject to single-indexed distortion. 103-120 - Zhensheng Huang, Zhen Pang, Tao Hu

:
Testing structural change in partially linear single-index models with error-prone linear covariates. 121-133 - Junhui Wang

, Yixin Fang:
Analysis of presence-only data via semi-supervised learning approaches. 134-143 - F. B. Gonçalves, Dani Gamerman, T. M. Soares

:
Simultaneous multifactor DIF analysis and detection in Item Response Theory. 144-160 - Cristian Villegas

, Gilberto A. Paula, Francisco José de A. Cysneiros, Manuel Galea
:
Influence diagnostics in generalized symmetric linear models. 161-170 - Donghwan Lee

, Youngjo Lee, Myunghee Cho Paik, Michael G. Kenward:
Robust inference using hierarchical likelihood approach for heavy-tailed longitudinal outcomes with missing data: An alternative to inverse probability weighted generalized estimating equations. 171-179 - Matthijs J. Warrens:

The Cicchetti-Allison weighting matrix is positive definite. 180-182 - M. C. Jones:

Erratum to: "On simulating Balakrishnan skew-normal variates" by Mahdi Teimouri and Saralees Nadarajah [Computational Statistics & Data Analysis 57 (2013) 52-58]. 183-184

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