
HdBCS
 Referenced in 78 articles
[sw29884]
 HdBCS  Highdimensional Bayesian Covariance Selection. This site provides C++ code software implementing...

gss
 Referenced in 284 articles
[sw06099]
 estimation with censored life time data and covariates. The unifying themes are the general penalized ... devoted to model construction, smoothing parameter selection, computation, and asymptotic convergence. Most of the computational...

CHOMPACK
 Referenced in 13 articles
[sw04593]
 algorithms in the paper Covariance selection for nonchordal graphs via chordal embedding...

tRNAscanSE
 Referenced in 16 articles
[sw08005]
 then analyzed by a highly selective tRNA covariance model. This work represents a practical application...

spatstat
 Referenced in 135 articles
[sw04429]
 Point Patterns, including multitype/marked points and spatial covariates, in any twodimensional spatial region. Also ... relative risk estimation with crossvalidated bandwidth selection, mark correlation functions, segregation indices, mark dependence ... Models may include dependence on covariates, interpoint interaction, cluster formation and dependence on marks. Fitted...

CMAES
 Referenced in 114 articles
[sw05063]
 stands for Covariance Matrix Adaptation Evolution Strategy. Evolution strategies (ES) are stochastic, derivativefree methods ... variation (via mutation and recombination) and selection: in each generation (iteration) new individuals (candidate solutions ... stochastic way, and then some individuals are selected for the next generation based on their ... this distribution are represented by a covariance matrix. The covariance matrix adaptation...

gRim
 Referenced in 3 articles
[sw20816]
 models for multivariate normal data (i.e. covariance selection models) Mixed interaction models...

OptiML
 Referenced in 3 articles
[sw05117]
 interface which solve the sparse inverse covariance selection problem. OptiML is released as open source...

piMASS
 Referenced in 17 articles
[sw17249]
 variable selection regression problem, with the SNPs as the covariates in the regression. Characteristic features...

CovSel
 Referenced in 2 articles
[sw24111]
 package CovSel: ModelFree Covariate Selection. Modelfree selection of covariates under unconfoundedness for situations...

stm
 Referenced in 8 articles
[sw30849]
 includes tools for model selection, visualization, and estimation of topiccovariate regressions. Methods developed...

SemiParSampleSel
 Referenced in 5 articles
[sw24025]
 interest. Classic sample selection models assume a priori that continuous covariates have a linear ... SemiParSampleSel which implements copula regression spline sample selection models. The proposed implementation ... deal with nonrandom sample selection, nonlinear covariateresponse relationships, and nonnormal bivariate...

crrstep
 Referenced in 2 articles
[sw28754]
 package crrstep: Stepwise Covariate Selection for the Fine & Gray Competing Risks Regression Model. Performs forward...

DEOD
 Referenced in 2 articles
[sw23965]
 driver genes based on a partial covariance selection method. DEOD uncovers the dominant effects...

multtest
 Referenced in 22 articles
[sw08262]
 hypotheses with tstatistics, users may also select a potentially faster null distribution which ... multivariate normal with mean zero and variance covariance matrix derived from the vector influence function...

qrcmNP
 Referenced in 1 article
[sw35602]
 penalized approach to covariate selection through quantile regression coefficient models. The coefficients of a quantile ... penalized method that can address the selection of covariates in this particular modelling framework. Unlike ... penalized quantile regression estimators, in which model selection is quantilespecific, our approach permits using...

BIONJ
 Referenced in 30 articles
[sw08301]
 firstorder model of the variances and covariances of evolutionary distance estimates. This model ... sequences. At each step it permits the selection, from the class of admissible reductions...

AS 105
 Referenced in 1 article
[sw03803]
 Algorithm AS 105. Fitting a covariance selection model to a matrix...

HS_GHS
 Referenced in 1 article
[sw38987]
 flexible, with multiple linear regression and covariance selection models being special cases. However, its practical ... both the mean vector and the inverse covariance matrix, a problem inherently more complex than...

PReMiuM
 Referenced in 12 articles
[sw14746]
 covariates actively drive the mixture components. This is implemented in the package as variable selection...