## File: residuals.gl1ce.Rd

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r-cran-lasso2 1.2-20-1
 12345678910111213141516171819202122232425262728293031323334353637383940414243 \name{residuals.gl1ce} \alias{residuals.gl1ce} \title{Compute Residuals for gl1ce' Objects} \description{ Computes one of the four types of residuals available for \code{gl1ce} objects. This is a method for the function residuals() for objects inheriting from class \code{gl1ce}. As several types of residuals are available for \code{gl1ce} objects, there is an additional optional argument type. } \usage{ \method{residuals}{gl1ce}(object, type=c("deviance", "pearson", "working", "response"), \dots) } \arguments{ \item{object}{ an object inheriting from class \code{gl1ce} representing a fitted model. } \item{type}{ type of residuals, with choices "deviance", "pearson", "working" or "response"; the first is the default. } \item{\dots}{possibly further arguments (none at the moment).} } \value{ A numeric vector of residuals. See Statistical Models in S for detailed definitions of each type of residual. The sum of squared deviance residuals add up to the deviance. The pearson residuals are standardized residuals on the scale of the response. The working residuals reside on the object, and are the residuals from the final fit. The response residuals are simply \code{y - fitted(object)}. The \code{summary()} method for \code{gl1ce} objects produces deviance residuals. The residuals component of a \code{gl1ce} object contains the working residuals. } \references{ Chambers, J.M., and Hastie, T.J. (1991). Statistical Models in S, pp. 204--206. } \seealso{\code{\link{gl1ce}} for examples; \code{\link{fitted.l1ce}} is used for fitted values. } \keyword{models} % Converted by Sd2Rd version 1.21. `