Approximate marginal inference for regression-scale models
Likelihood inference based on higher order approximations for linear nonnormal regression models 1.1
package
Package: | marg |
Version: | 1.2-0 |
Date: | 2009-10-03 |
Depends: | R (>= 2.6.0), statmod, survival |
Suggests: | boot, cond, csampling, nlreg |
License: | GPL (>= 2) |
URL: | http://www.r-project.org, http://statwww.epfl.ch/AA/ |
LazyLoad: | yes |
LazyData: | yes |
Index:
Functions:
=========
cond Approximate Conditional Inference - Generic
Function
cond.rsm Approximate Conditional Inference in
Regression-Scale Models
dHuber Huber's Least Favourable Distribution
family.rsm Use family() on a "rsm" object
family.rsm.object Family Object for Regression-Scale Models
logLik.rsm Compute the Log Likelihood for
Regression-Scale Models
marg.object Approximate Marginal Inference Object
plot.marg Generate Plots for an Approximate Marginal
Inference Object
print.summary.marg Use print() on a "summary.marg" object
residuals.rsm Compute Residuals for Regression-Scale Models
rsm Fit a Regression-Scale Model
rsm.diag Diagnostics for Regression-Scale Models
rsm.diag.plots Diagnostic Plots for Regression-Scale Models
rsm.families Generate a RSM Family Object
rsm.fit Fit a Regression-Scale Model Without Computing
the Model Matrix
rsm.null Fit an Empty Regression-Scale Model
rsm.object Regression-Scale Model Object
rsm.surv Fit a Regression-Scale Model Without Computing
the Model Matrix
summary.marg Summary Method for Objects of Class "marg"
summary.rsm Summary Method for Regression-Scale Models
update.rsm Update and Re-fit a RSM Model Call
vcov.rsm Calculate Variance-Covariance Matrix for a
Fitted RSM Model
Datasets:
========
darwin Darwin's Data on Growth Rates of Plants
houses House Price Data
nuclear Nuclear Power Station Data
venice Sea Level Data
Further information is available in the following vignettes:
Rnews-paper | hoa: An R Package Bundle for Higher Order Likelihood Inference (source, pdf) |
S original by Alessandra R. Brazzale alessandra.brazzale@unimore.it. R port by Alessandra R. Brazzale alessandra.brazzale@unimore.it, following earlier work by Douglas Bates.
Maintainer: Alessandra R. Brazzale alessandra.brazzale@unimore.it