Package: reglogit 1.2-7

reglogit: Simulation-Based Regularized Logistic Regression

Regularized (polychotomous) logistic regression by Gibbs sampling. The package implements subtly different MCMC schemes with varying efficiency depending on the data type (binary v. binomial, say) and the desired estimator (regularized maximum likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a unified interface. For details, see Gramacy & Polson (2012 <doi:10.1214/12-BA719>).

Authors:Robert B. Gramacy <[email protected]>

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19 exports 0.00 score 4 dependencies 4 scripts 256 downloads

Last updated 1 years agofrom:2d19b31353. Checks:OK: 1 NOTE: 8. Indexed: yes.

Exports:beta.dRUMcalc.Cscalc.lpostcalc.mlpostdraw.betadraw.lambdadraw.nudraw.omegadraw.zgibbs.dRUMmpreprocessmy.rinvgausspredict.reglogitpredict.regmlogitpreprocessreglogitregmlogitrmultnormz.dRUM

Dependencies:bootlatticeMatrixmvtnorm