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  • Committer: Package Import Robot
  • Author(s): Chris Lawrence
  • Date: 2011-11-04 13:13:06 UTC
  • mfrom: (1.2.9)
  • mto: This revision was merged to the branch mainline in revision 14.
  • Revision ID: package-import@ubuntu.com-20111104131306-w9fd83i51rw60gxf
Tags: upstream-0.8-4
Import upstream version 0.8-4

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R/predict.vglm.q
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predict.vglm = function(object,
 
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predictvglm = function(object,
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                        newdata=NULL,
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                        type=c("link", "response", "terms"),
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                        se.fit=FALSE,
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    }
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    if (deriv != 0)
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        stop("'deriv' must be 0 for predict.vglm()")
 
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        stop("'deriv' must be 0 for predictvglm()")
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    if (mode(type) != "character" && mode(type) != "name")
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        type = as.character(substitute(type))
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                                           type=type, se.fit=se.fit,
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                                           deriv=deriv, 
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                                           dispersion=dispersion, ...) 
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                   fv = object@family@inverse(predictor, extra)
 
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                   fv = object@family@linkinv(predictor, extra)
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                   dimnames(fv) = list(dimnames(fv)[[1]],
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                                       dimnames(object@fitted.values)[[2]])
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                   fv
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                       M = object@misc$M
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                       fv = object@family@inverse(predictor, extra)
 
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                       fv = object@family@linkinv(predictor, extra)
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                       if (M > 1 && is.matrix(fv)) {
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                           dimnames(fv) = list(dimnames(fv)[[1]],
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                                          dimnames(object@fitted.values)[[2]])
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setMethod("predict", "vglm", function(object, ...) 
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    predict.vglm(object, ...))
 
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    predictvglm(object, ...))
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                                             type=type, se.fit=se.fit,
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                                             deriv=deriv, 
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                                             dispersion=dispersion, ...) 
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                  fv = object@family@inverse(predictor, extra)
 
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                  fv = object@family@linkinv(predictor, extra)
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                  dimnames(fv) = list(dimnames(fv)[[1]],
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                                       dimnames(object@fitted.values)[[2]])
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                  fv
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                }
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              )
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    } else {
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        return(predict.vglm(object, newdata=newdata,
 
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        return(predictvglm(object, newdata=newdata,
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                            type=type, se.fit=se.fit,
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                            deriv=deriv, 
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                            dispersion=dispersion, ...))