[R] A suggestion for predict function(s)

[Ross Darnell]

Liaw, Andy wrote:
> I must respectfully disagree.  Why carry extra copies of data arround?  This
> is probably OK for small to medium sized data, but definitely not for large
> data.
> 
> Besides, in your example, it may do different things depending on whether
> newdata is supplied:  model.matrix is not necessarily the same as the
> original data frame.  You need a bit more work to get the right model.matrix
> that correspond to the newdata.  It's not clear to me whether you want to
> return model matrix or model frame, but in either case it's not sufficient
> to just use `newdata'.
> 
> Andy
> 
> 
>>From: Ross Darnell
>>
>>Maybe a useful addition to the predict functions would be to 
>>return the 
>>values of the predictor variables. It just (unless there are 
>>problems) 
>>requires an extra line. I have inserted an example below.
>>
>>"predict.glm" <-
>>   function (object, newdata = NULL, type = c("link", "response",
>>                                       "terms"), se.fit = FALSE, 
>>dispersion = NULL, terms = NULL,
>>             na.action = na.pass, ...)
>>{
>>   type <- match.arg(type)
>>   na.act <- object$na.action
>>   object$na.action <- NULL
>>   if (!se.fit) {
>>     if (missing(newdata)) {
>>       pred <- switch(type, link = object$linear.predictors,
>>                      response = object$fitted, terms = 
>>predict.lm(object,
>>                                                  se.fit = 
>>se.fit, scale 
>>= 1, type = "terms",
>>                                                  terms = terms))
>>       if (!is.null(na.act))
>>         pred <- napredict(na.act, pred)
>>     }
>>     else {
>>       pred <- predict.lm(object, newdata, se.fit, scale = 1,
>>                          type = ifelse(type == "link", 
>>"response", type),
>>                          terms = terms, na.action = na.action)
>>       switch(type, response = {
>>         pred <- family(object)$linkinv(pred)
>>       }, link = , terms = )
>>     }
>>   }
>>   else {
>>     if (inherits(object, "survreg"))
>>       dispersion <- 1
>>     if (is.null(dispersion) || dispersion == 0)
>>       dispersion <- summary(object, dispersion = 
>>dispersion)$dispersion
>>     residual.scale <- as.vector(sqrt(dispersion))
>>     pred <- predict.lm(object, newdata, se.fit, scale = 
>>residual.scale,
>>                        type = ifelse(type == "link", 
>>"response", type),
>>                        terms = terms, na.action = na.action)
>>     fit <- pred$fit
>>     se.fit <- pred$se.fit
>>     switch(type, response = {
>>       se.fit <- se.fit * abs(family(object)$mu.eta(fit))
>>       fit <- family(object)$linkinv(fit)
>>     }, link = , terms = )
>>     if (missing(newdata) && !is.null(na.act)) {
>>       fit <- napredict(na.act, fit)
>>       se.fit <- napredict(na.act, se.fit)
>>     }
>>     predictors <- if (missing(newdata)) model.matrix(object) 
>>else newdata
>>     pred <- list(predictors=predictors,
>>                  fit = fit, se.fit = se.fit,
>>                  residual.scale = residual.scale)
>>   }
>>   pred
>>
>>
>>#______________________ end of R code
>>
>>
>>
>>Ross Darnell
>>-- 
>>School of Health and Rehabilitation Sciences
>>University of Queensland, Brisbane QLD 4072 AUSTRALIA
>>Email: <r.darnell at uq.edu.au>
>>Phone: +61 7 3365 6087     Fax: +61 7 3365 4754  Room:822, 
>>Therapies Bldg.
>>http://www.shrs.uq.edu.au/shrs/school_staff/ross_darnell.html
>>
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>>
>>
>>
> 
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