Compute Predictions for a Logistic Regression Model from Spotfire

logisticRegPredict

Description

Computes predictions for a logistic regression model from Spotfire using the data in newdata. This function is not intended to be called by the user.

Usage

logisticRegPredict(modelObj, newdata, origPredNames, newPredNames)

Arguments

modelObj	an object of class "glm" that was fit with binomial family.
newdata	a data frame to use for the predictions. It must contain columns with names newPredNames.
origPredNames	a single character string containing the predictor variables used in modelObj. The values must be tab delimited.
newPredNames	a single character string naming the predictor variable in newdata. This is often the same as origPredNames. The values must be tab delimited.

Details

This function gets invoked when predictions for a logistic regression model are requested in Spotfire.

Value

a data frame containing the prediction probabilities and predicted class.

Examples

library(Sdatasets)  # for the kyphosis data
zglm <- logisticRegFit(Kyphosis ~ Age + Number + Start, data=kyphosis,
    modelName="glmExample", responseLevel="absent")
predNamesString <- zglm$fitSummaryTable[2, 1]
predNames <- strsplit(predNamesString, "\t", fixed=TRUE)[[1]]
kyph <- kyphosis[1:20, predNames]
zgPred <- logisticRegPredict(zglm$modelObj, newdata=kyph,
    predNamesString, predNamesString)

Package SpotfireStats version 6.1.1-7
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