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datadr (version 0.8.6.1)

drGLM: GLM Transformation Method

Description

GLM transformation method -- Fit a generalized linear model to each subset

Usage

drGLM(...)

Arguments

arguments you would pass to the glm function

Value

An object of class drCoef that contains the glm coefficients and other data needed by combMeanCoef

Details

This provides a transformation function to be called for each subset in a recombination MapReduce job that applies R's glm method and outputs the coefficients in a way that combMeanCoef knows how to deal with. It can be applied to a ddf with addTransform prior to calling recombine.

See Also

divide, recombine, rrDiv

Examples

Run this code
# NOT RUN {
# Artificially dichotomize the Sepal.Lengths of the iris data to
# demonstrate a GLM model
irisD <- iris
irisD$Sepal <- as.numeric(irisD$Sepal.Length > median(irisD$Sepal.Length))

# Divide the data
bySpecies <- divide(irisD, by = "Species")

# A function to fit a logistic regression model to each species
logisticReg <- function(x)
  drGLM(Sepal ~ Sepal.Width + Petal.Length + Petal.Width,
        data = x, family = binomial())

# Apply the transform and combine using 'combMeanCoef'
bySpecies %>%
  addTransform(logisticReg) %>%
  recombine(combMeanCoef)

# }

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