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Tests for High Dimensional Generalized Linear Models
Generalized Linear Model Gene-Sets High Dimensional Covariate Nuisance Parameter U-statistics
2016/1/26
We consider testing regression coefficients in high dimensional generalized linear mod-els. By modifying a test statistic proposed by Goeman et al. (2011) for large but fixed dimensional settings, we ...
Tests for High Dimensional Generalized Linear Models
Generalized Linear Model Gene-Sets High Dimensional Covariate Nuisance Parameter U-statistics
2016/1/20
We consider testing regression coefficients in high dimensional generalized linear mod-els. By modifying a test statistic proposed by Goeman et al. (2011) for large but fixed dimensional settings, we ...
Fast inference in generalized linear models via expected log-likelihoods
Fast inference generalized linear models expected log-likelihoods
2013/6/14
Generalized linear models play an essential role in a wide variety of statistical applications. This paper discusses an approximation of the likelihood in these models that can greatly facilitate comp...
An Active Set Algorithm to Estimate Parameters in Generalized Linear Models with Ordered Predictors
ordered explanatory variable constrained estimation least squares logistic regression Coxregression active set algorithm
2010/3/18
In biomedical studies, researchers are often interested in assessing the association between one or more ordinal explanatory variables and an outcome variable, at the same time adjusting for covariate...
Sure Independence Screening in Generalized Linear Models with NP-Dimensionality
generalized linear models independent learning sure indepen-dent screening variable selection
2010/3/19
Ultrahigh dimensional variable selection plays an increasingly
important role in contemporary scientific discoveries and statisti-
cal research. Among others, Fan and Lv (2008) propose an indepen-
...
Bayesian Variable Selection and Computation for Generalized Linear Models with Conjugate Priors
Bayes factor Conditional Predictive Ordinate Conjugate prior Poisson regression Logistic regression
2009/9/22
In this paper, we consider theoretical and computational connections
between six popular methods for variable subset selection in generalized linear
models (GLMs) Under the conjugate priors develope...
Factorial experimental designs and generalized linear models
generalized linear model exponential family Fisher-Scoring algorithm factorial designs regular fraction
2009/2/23
This paper deals with experimental designs adapted to a generalized linear model. We introduce a special link function for which the orthogonality of design matrix obtained under Gaussian assumption i...
Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models
Bayesian analysis Double exponential family Hierarchical priors Variance estimation
2010/4/30
Flexibly modeling the response variance in regression is important for efficient parameter
estimation, correct inference, and for understanding the sources of variability in
the response. Our articl...
Design Issues for Generalized Linear Models：A Review
Bayesian design dependence on unknownparameters locally optimal design logistic regression response surfacemethodology
2010/4/26
Generalized linear models (GLMs) have been used quite effectively
in the modeling of a mean response under nonstandard conditions,
where discrete as well as continuous data distributions can be
acc...