\name{addvar} \alias{addvar} \title{ Added Variable Plot for Point Process Model } \description{ Computes the coordinates for an Added Variable Plot for a fitted point process model. } \usage{ addvar(model, covariate, ..., subregion=NULL, bw="nrd0", adjust=1, from=NULL, to=NULL, n=512, bw.input = c("points", "quad"), bw.restrict = FALSE, covname, crosscheck=FALSE) } \arguments{ \item{model}{ Fitted point process model (object of class \code{"ppm"}). } \item{covariate}{ The covariate to be added to the model. Either a pixel image, a \code{function(x,y)}, or a character string giving the name of a covariate that was supplied when the model was fitted. } \item{subregion}{ Optional. A window (object of class \code{"owin"}) specifying a subset of the spatial domain of the data. The calculation will be confined to the data in this subregion. } \item{bw}{ Smoothing bandwidth or bandwidth rule (passed to \code{\link[stats]{density.default}}). } \item{adjust}{ Smoothing bandwidth adjustment factor (passed to \code{\link[stats]{density.default}}). } \item{n, from, to}{ Arguments passed to \code{\link[stats]{density.default}} to control the number and range of values at which the function will be estimated. } \item{\dots}{ Additional arguments passed to \code{\link[stats]{density.default}}. } \item{bw.input}{ Character string specifying the input data used for automatic bandwidth selection. } \item{bw.restrict}{ Logical value, specifying whether bandwidth selection is performed using data from the entire spatial domain or from the \code{subregion}. } \item{covname}{ Optional. Character string to use as the name of the covariate. } \item{crosscheck}{ For developers only. Logical value indicating whether to perform cross-checks on the validity of the calculation. } } \details{ This command generates the plot coordinates for an Added Variable Plot for a spatial point process model. Added Variable Plots (Cox, 1958, sec 4.5; Wang, 1985) are commonly used in linear models and generalized linear models, to decide whether a model with response \eqn{y} and predictors \eqn{x} would be improved by including another predictor \eqn{z}. In a (generalised) linear model with response \eqn{y} and predictors \eqn{x}, the Added Variable Plot for a new covariate \eqn{z} is a plot of the smoothed Pearson residuals from the original model against the scaled residuals from a weighted linear regression of \eqn{z} on \eqn{x}. If this plot has nonzero slope, then the new covariate \eqn{z} is needed. For general advice see Cook and Weisberg(1999); Harrell (2001). Essentially the same technique can be used for a spatial point process model (Baddeley et al, 2012). The argument \code{model} should be a fitted spatial point process model (object of class \code{"ppm"}). The argument \code{covariate} identifies the covariate that is to be considered for addition to the model. It should be either a pixel image (object of class \code{"im"}) or a \code{function(x,y)} giving the values of the covariate at any spatial location. Alternatively \code{covariate} may be a character string, giving the name of a covariate that was supplied (in the \code{covariates} argument to \code{\link{ppm}}) when the model was fitted, but was not used in the model. The result of \code{addvar(model, covariate)} is an object belonging to the classes \code{"addvar"} and \code{"fv"}. Plot this object to generate the added variable plot. Note that the plot method shows the pointwise significance bands for a test of the \emph{null} model, i.e. the null hypothesis that the new covariate has no effect. The smoothing bandwidth is controlled by the arguments \code{bw}, \code{adjust}, \code{bw.input} and \code{bw.restrict}. If \code{bw} is a numeric value, then the bandwidth is taken to be \code{adjust * bw}. If \code{bw} is a string representing a bandwidth selection rule (recognised by \code{\link[stats]{density.default}}) then the bandwidth is selected by this rule. The data used for automatic bandwidth selection are specified by \code{bw.input} and \code{bw.restrict}. If \code{bw.input="points"} (the default) then bandwidth selection is based on the covariate values at the points of the original point pattern dataset to which the model was fitted. If \code{bw.input="quad"} then bandwidth selection is based on the covariate values at every quadrature point used to fit the model. If \code{bw.restrict=TRUE} then the bandwidth selection is performed using only data from inside the \code{subregion}. } \value{ An object of class \code{"addvar"} containing the coordinates for the added variable plot. There is a \code{plot} method. } \section{Internal data}{ The return value has an attribute \code{"spatial"} which contains the internal data: the computed values of the residuals, and of all relevant covariates, at each quadrature point of the model. It is an object of class \code{"ppp"} with a data frame of marks. } \references{ Baddeley, A. and Chang, Y.-M. and Song, Y. and Turner, R. (2012) \emph{Residual diagnostics for covariate effects in spatial point process models}. Submitted for publication. Cook, R.D. and Weisberg, S. (1999) \emph{Applied regression, including computing and graphics}. New York: Wiley. Cox, D.R. (1958) \emph{Planning of Experiments}. New York: Wiley. Harrell, F. (2001) \emph{Regression Modeling Strategies}. New York: Springer. Wang, P. (1985) Adding a variable in generalized linear models. \emph{Technometrics} \bold{27}, 273--276. } \author{ Adrian Baddeley \email{Adrian.Baddeley@csiro.au} \url{http://www.maths.uwa.edu.au/~adrian/}, Rolf Turner \email{r.turner@auckland.ac.nz}, Ya-Mei Chang and Yong Song. } \seealso{ \code{\link{parres}}, \code{\link{rhohat}}, \code{\link{rho2hat}}. } \examples{ X <- rpoispp(function(x,y){exp(3+3*x)}) model <- ppm(X, ~y) adv <- addvar(model, "x") plot(adv) adv <- addvar(model, "x", subregion=square(0.5)) } \keyword{spatial} \keyword{models}