Langrock R, King R. Maximum likelihood estimation of mark–recapture–recovery models in the presence of continuous covariates. Ann. Appl. Stat. 2013;7(3):1709-1732
This paper considers Maximum Likelihood (ML) based estimation and inference procedures for linear dy...
We study parameter estimation in linear Gaussian covariance models, which are p-dimensional Gaussian...
Cook and Forzani (2008) proposed covariance reducing models as a method for modeling the differences...
We consider mark-recapture-recovery (MRR) data of animals where the model parameters are a function ...
Mews S, Langrock R, Ötting M, Yaqine H, Reinecke J. Maximum approximate likelihood estimation of gen...
This article investigates the Farlie–Gumbel–Morgenstern class of models for ex-changeable continuous...
AbstractA unified approach of treating multivariate linear normal models is presented. The results o...
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
This paper deals with multivariate Gaussian models for which the covariance matrix is a Kronecker pr...
The subject of this article is to present the beta – regression model, where we assume that one para...
In this article models based on pq-dimensional normally distributed ran-dom vectors x are studied wi...
Michelot T, Langrock R, Kneib T, King R. Maximum penalized likelihood estimation in semiparametric m...
A maximum likelihood (ML) estimation procedure is developed to find the mean of the exponential fami...
A multivariate spatial linear coregionalization model is considered that incorporates the Matérn cl...
<p>Maximum-likelihood estimates of the land-use diversity of the stochastic frontier Cobb-Douglas pr...
This paper considers Maximum Likelihood (ML) based estimation and inference procedures for linear dy...
We study parameter estimation in linear Gaussian covariance models, which are p-dimensional Gaussian...
Cook and Forzani (2008) proposed covariance reducing models as a method for modeling the differences...
We consider mark-recapture-recovery (MRR) data of animals where the model parameters are a function ...
Mews S, Langrock R, Ötting M, Yaqine H, Reinecke J. Maximum approximate likelihood estimation of gen...
This article investigates the Farlie–Gumbel–Morgenstern class of models for ex-changeable continuous...
AbstractA unified approach of treating multivariate linear normal models is presented. The results o...
Abstract. The subject of this article is to present the beta – regression model, where we assume tha...
This paper deals with multivariate Gaussian models for which the covariance matrix is a Kronecker pr...
The subject of this article is to present the beta – regression model, where we assume that one para...
In this article models based on pq-dimensional normally distributed ran-dom vectors x are studied wi...
Michelot T, Langrock R, Kneib T, King R. Maximum penalized likelihood estimation in semiparametric m...
A maximum likelihood (ML) estimation procedure is developed to find the mean of the exponential fami...
A multivariate spatial linear coregionalization model is considered that incorporates the Matérn cl...
<p>Maximum-likelihood estimates of the land-use diversity of the stochastic frontier Cobb-Douglas pr...
This paper considers Maximum Likelihood (ML) based estimation and inference procedures for linear dy...
We study parameter estimation in linear Gaussian covariance models, which are p-dimensional Gaussian...
Cook and Forzani (2008) proposed covariance reducing models as a method for modeling the differences...
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