drGLM: GLM Transformation Method
In datadr: Divide and Recombine for Large, Complex Data

Description Usage Arguments Details Value Author(s) See Also Examples

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

1	drGLM(...)

...

arguments you would pass to the glm function

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.

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

Ryan Hafen

divide, recombine, rrDiv

# 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)