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% Generated by roxygen2: do not edit by hand% Please edit documentation in R/mgcvExports.R\name{dDeta}\alias{dDeta}\title{Obtaining derivative w.r.t. linear predictor}\usage{dDeta(y, mu, wt, theta, fam, deriv = 0)}\arguments{\item{y}{vector of observations.}\item{mu}{if \code{eta} is the linear predictor, \code{mu = inv_link(eta)}. In a traditional GAM \code{mu=E(y)}.}\item{wt}{vector of weights.}\item{theta}{vector of family parameters that are not regression coefficients (e.g. scale parameters).}\item{fam}{the family object.}\item{deriv}{the order of derivative of the smoothing parameter score required.}}\value{A list of derivatives.}\description{INTERNAL function. Distribution families provide derivatives of the deviance and link w.r.t. \code{mu = inv_link(eta)}.This routine converts these to the required derivatives of the deviance w.r.t. eta, the linear predictor.}\author{Simon N. Wood <simon.wood@r-project.org>.}