Logistic Regression with Maximum Likelihood Estimation
Fit a logistic regression model using maximum likelihood estimation
ml.rgr(dataset)
dataset |
a |
This function is a wrapper for glm.fit
, for convenient
application within several functions in the apricomp package. This function may
be called directly. For regression with an intercept included, the first column in
the dataset must be a column of 1s.
The function returns a column-vector containing the logistic regression coefficients and intercept (if specified).
## Logistic regression using a subset of the mtcars data (outcome is "vs") data(mtcars) mtc.df <- mtcars[, c(8, 1, 9)] mtc.shaped <- datashape(dataset = mtc.df, y = 1) ml.rgr(mtc.shaped) ml.rgr(cbind(1,mtc.shaped))
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