lrm.fit.bare
Bare Bones Logistic Regression Fit
lrm.fit.bare(x, y, maxit = 12, eps = 0.025, tol = 1e-07)
x |
a vector of matrix of covariate values |
y |
a numeric or factor vector representing the dependent variable |
maxit |
maximum number of iteractions |
eps |
stopping criterion (change in -2 log likelihood) |
tol |
matrix inversion tolerance for singularities |
This is a stripped down version of the lrm.fit() function that computes only the regression coefficients, variance-covariance-matrix, and log likelihood (for null and fitted model) and does not compute any model fit indexes etc. This is for speed in simulations or with bootstrapping. Missing data are not allowed. The function handles binary and ordinal logistic regression (proportional odds model).
a list with elements coefficients, var, fail, freq, deviance
Frank Harrell
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