搜索结果: 1-9 共查到“统计逻辑学 likelihood”相关记录9条 . 查询时间(0.25 秒)
MCMC methods for Gaussian process models using fast approximations for the likelihood
MCMC methods for Gaussian process models using fast approximations for the likelihood
2013/6/14
Gaussian Process (GP) models are a powerful and flexible tool for non-parametric regression and classification. Computation for GP models is intensive, since computing the posterior density, $\pi$, fo...
MCMC methods for Gaussian process models using fast approximations for the likelihood
MCMC methods for Gaussian process models using fast approximations for the likelihood
2013/6/14
Gaussian Process (GP) models are a powerful and flexible tool for non-parametric regression and classification. Computation for GP models is intensive, since computing the posterior density, $\pi$, fo...
Joint likelihood calculation for intervention and observational data from a Gaussian Bayesian network
Gaussian Bayesian networks causal effects intervention data Fisher information
2013/6/13
Methodological development for the inference of gene regulatory networks from transcriptomic data is an active and important research area. Several approaches have been proposed to infer relationships...
Model selection and clustering in stochastic block models with the exact integrated complete data likelihood
Random graphs stochastic block models integrated classication likelihood
2013/4/27
The stochastic block model (SBM) is a mixture model used for the clustering of nodes in networks. It has now been employed for more than a decade to analyze very different types of networks in many sc...
Penalized Likelihood and Bayesian Function Selection in Regression Models
generalized additive model regularization smoothing spike and slab priors
2013/4/27
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonl...
Penalized Likelihood and Bayesian Function Selection in Regression Models
generalized additive model regularization smoothing spike and slab priors
2013/4/27
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonl...
Generalized Likelihood Ratio Statistics and Uncertainty Adjustments in Efficient Adaptive Design of Clinical Trials
Hoeffding’s information bound Internal pilot Kullback-Leibler information Modified Haybittle-Peto test Multiparameter exponential family Sample size re-estimation
2011/6/20
A new approach to adaptive design of clinical trials is proposed in a general multi-
parameter exponential family setting, based on generalized likelihood ratio statistics and optimal
sequential tes...
Adjusted empirical likelihood with high-order precision
Bartlett correction confidence region Edgeworth expansion
2010/10/14
Empirical likelihood is a popular nonparametric or semi-parametric statistical method with many nice statistical properties. Yet when the sample size is small, or the dimension of the accompanying est...
Likelihood Inference for Models with Unobservables: Another View
Hierarchical generalized linear model unobservables random effects likelihood
2010/10/14
There have been controversies among statisticians on (i) what to model and (ii) how to make inferences from models with unobservables. One such controversy concerns the difference between estimation ...