[Lme4-commits] r1428 - pkg/lme4Eigen/man

[noreply at r-forge.r-project.org]

Author: dmbates
Date: 2011-10-18 22:32:54 +0200 (Tue, 18 Oct 2011)
New Revision: 1428

Added:
   pkg/lme4Eigen/man/lmResp-class.Rd
Log:
Document response reference classes and constructor objects


Added: pkg/lme4Eigen/man/lmResp-class.Rd
===================================================================
--- pkg/lme4Eigen/man/lmResp-class.Rd	                        (rev 0)
+++ pkg/lme4Eigen/man/lmResp-class.Rd	2011-10-18 20:32:54 UTC (rev 1428)
@@ -0,0 +1,127 @@
+\name{lmResp-class}
+\alias{lmResp-class}
+\alias{glmResp-class}
+\alias{lmerResp-class}
+\alias{nlsResp-class}
+\alias{lmResp}
+\alias{glmResp}
+\alias{nlsResp}
+\alias{lmerResp}
+\title{Classes \code{"lmResp"}, \code{"glmResp"}, \code{"nlsResp"} and \code{"lmerResp"}}
+\usage{
+  lmResp$new(y=y)
+}
+\description{
+  Reference classes for response modules, including linear models,
+  \code{"lmResp"}, generalized linear models, \code{"glmResp"},
+  nonlinear models, \code{"nlsResp"} and linear mixed-effects models,
+  \code{"lmerResp"}.  Each reference class is associated with a C++
+  class of the same name.  As is customary, the generator object for
+  each class has the same name as the class.
+}
+\section{Extends}{
+  All reference classes extend and inherit methods from
+  \code{"\linkS4class{envRefClass}"}.  Furthermore, \code{"glmResp"},
+  \code{"nlsResp"} and \code{"lmerResp"} all extend the \code{"lmResp"}
+  class. 
+}
+%\references{}
+%\author{}
+\note{
+  Objects from these reference classes correspond to objects in C++ classes.
+  Methods are invoked on the C++ classes using the external pointer in
+  the \code{ptr} field.  When saving such an object the external pointer
+  is converted to a null pointer, which is why there are redundant
+  fields containing enough information as R objects to be able to
+  regenerate the C++ object.  The convention is that a field whose name begins
+  with an upper-case letter is an R object and the corresponding field
+  whose name begins with the lower-case letter is an active-binding
+  function.  The values should be accessed through the active-binding
+  function, not directly as the R object field.
+}
+\seealso{
+  \code{\link{lmer}}, \code{\link{glmer}}, \code{\link{nlmer}}, \code{\linkS4class{merMod}}.
+}
+\examples{
+showClass("lmResp")
+str(lmResp$new(y=1:4))
+showClass("glmResp")
+str(glmResp$new(family=poisson(), y=1:4))
+showClass("nlsResp")
+showClass("lmerResp")
+str(lmerResp$new(y=1:4))
+}
+\keyword{classes}
+\section{Fields}{
+  For class \code{"lmResp"},
+  \describe{
+    \item{\code{y}:}{\code{numeric} response vector }
+    \item{\code{Ptr}:}{\code{externalptr} to the instance of the C++ class}
+    \item{\code{ptr}:}{\code{activeBindingFunction} that returns the
+      external pointer, \code{Ptr}, regenerating it if necessary.  All
+      access to the external pointer should be through this field.}
+    \item{\code{Offset}:}{\code{numeric} vector representing the offset
+      in the model.  A numeric vector of length 0 indicates no offset.}
+    \item{\code{offset}:}{\code{activeBindingFunction} returning the
+      offset.  This always returns a vector of the same length as the
+      linear predictor.}
+    \item{\code{Weights}:}{\code{numeric} vector of (prior) case
+      weights. A numeric vector of length 0 indicates equal prior weights.}
+    \item{\code{weights}:}{\code{activeBindingFunction} returning the
+      prior case weights.  This always returns a vector of the same
+      length as the response.}
+  }
+  Additional fields in class \code{"glmResp"},
+  \describe{
+    \item{\code{family}:}{A glm \code{family}, see \code{\link{family}}}
+    \item{\code{N}:}{\code{integer} vector of number of individual
+      observations per collapsed observation.  Only meaningful for the
+      \code{\link{binomial}} family.}
+    \item{\code{n}:}{\code{activeBindingFunction} to extract the
+      \code{n} vector.  Always returns an integer vector of the same
+      length as the response.}
+  }
+}
+\section{Methods}{
+  For class \code{"lmResp"},
+  \describe{
+    \item{\code{sqrtrwt()}:}{returns the square root of the residual weights}
+    \item{\code{updateMu(gamma)}:}{update the mean response given the
+      linear predictor \code{gamma}.  Returns the weighted residual sum of
+      squares.}
+    \item{\code{wrss()}:}{returns the weighted residual sum of
+      squares.}
+    \item{\code{fitted()}:}{returns the current value of the mean response.}
+    \item{\code{wtres()}:}{returns the vector of the weighted residuals.}
+    \item{\code{sqrtXwt()}:}{returns a vector of weights for the
+      predictor model matrices.}
+  }
+  Additional methods for class \code{"glmResp"}
+  \describe{
+    \item{\code{sqrtWrkWt()}:}{\code{numeric} matrix of one column
+      giving the square root of the working weights for the model matrices.}
+    \item{\code{resDev()}:}{the residual deviance (i.e. the sum of the
+      deviance residuals). }
+    \item{\code{wrkResids()}:}{\code{numeric} vector of working residuals.}
+    \item{\code{link()}:}{\code{character} string - the name of link.} 
+    \item{\code{allInfo()}:}{a data frame whose columns are all the
+      quantities of interest that are represented as numeric vectors of
+      the same length as the response.}
+    \item{\code{updateWts()}:}{cause the residual weights and the model
+      matrix weights to be updated to the values corresponding to the
+      current mean response.}
+    \item{\code{muEta()}:}{the diagonal of the Jacobian matrix
+      \eqn{d\mu/d\eta}{d mu/d eta}.}
+    \item{\code{variance()}:}{\code{numeric} vector of case variances.}
+    \item{\code{devResid()}:}{\code{numeric} vector of deviance residuals.}
+    \item{\code{fam()}:}{\code{character} stirng - the name of the family.}
+    \item{\code{wrkResp()}:}{\code{numeric} vector of the working responses.}
+    \item{\code{eta()}:}{\code{numeric} vector of the linear predictor values.}
+    \item{\code{Laplace(ldL2, ldRX2, sqrL)}:}{returns the Laplace
+      approximation to the deviance.  The arguments are the logarithm of
+      the square of the determinant of the sparse Cholesky factor, \eqn{\mathbf{L}}{L},
+      the logarithm of the square of the determinant of the sparse Cholesky
+      factor, \eqn{\mathbf{R}_X}{RX}, (not used) and the squared length of
+      the orthogonal random effects vector, \eqn{\mathbf{u}}{u}.}
+  }
+}