| ¡@corresponding author* |
| Composite Likelihood Methods |
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Introduction to Special Issue
Nancy Reid, Bruce Lindsay and Kung-Yee Liang |
1 |
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An overview of composite likelihood methods
Cristiano Varin*, Nancy Reid and David Firth |
5 |
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On composite likelihoods in statistical genetics
F. Larribe* and P. Fearnhead |
43 |
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Issues and strategies in the selection of composite likelihoods
Bruce G. Lindsay, Grace Y. Yi* and Jianping Sun |
71 |
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Maximum local partial likelihood estimators for the counting process
intensity function and its derivatives
Feng Chen* |
107 |
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Adjusting composite likelihood ratio statistics
Luigi Pace, Alessandra Salvan* and Nicola Sartori |
129 |
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Bayesian composite marginal likelihoods
Francesco Pauli, Walter Racugno and Laura Ventura* |
149 |
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Composite likelihood EM algorithm with applications to multivariate
hidden Markov model
Xin Gao* and Peter X.-K. Song |
165 |
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Pseudo-likelihood estimation for incomplete data
Geert Molenberghs*, Michael G. Kenward, Geert Verbeke and Teshome Birhanu |
187 |
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A pairwise likelihood method for correlated binary data with/without
missing observations under generalized partially linear single-index
models
Wenqing He and Grace Y. Yi* |
207 |
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An EM composite likelihood approach for multistage sampling of family
data
Y. Choi* and L. Briollais |
231 |
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Comments on pairwise likelihood in time series models
Richard A. Davis and Chun Yip Yau* |
255 |
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Composite likelihood for time series models with a latent autoregressive
process
Chi Tim Ng, Harry Joe*, Dimitris Karlis and Juxin Liu |
279 |
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Nuisance parameters, composite likelihoods and a panel of GARCH
models
Cavit Pakel, Neil Shephard* and Kevin Sheppard |
307 |
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Extending pseudo-likelihood for Potts models
Saisuke Okabayashi*, Leif Johnson and Charles J. Geyer |
331 |
General |
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Semi-parametric inference for copula models for truncated data
Takeshi Emura, Weijing Wang* and Hui-Nien Hung |
349 |
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Theory of Gaussian variational approximation for a Poisson mixed model
Peter Hall, J. T. Ormerod and M. P. Wand* |
369 |
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Nonconcave penalized M-estimation with a diverging number of
parameters
Gaorong Li, Heng Peng* and Lixing Zhu |
391 |
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Optimality criteria for multiresponse linear models based on predictive
ellipsoids
Xin Liu, Rong-Xian Yue* and Fred J. Hickernell |
421 |
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Frequency properties of inferences based on an integrated likelihood
function
Thomas A. Severini* |
433 |
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Empirical Bayesian thresholding for sparse signals using mixture loss
functions
Vikas C. Raykar and Linda H. Zhao* |
449 |