Description Usage Arguments Value Examples
Carry our the Newton-Raphson optimization of the parameters for given weights via numeric approximations,
1 2 |
b |
The starting parameters. |
x |
An n-by-p design matrix. |
y |
A vector of observation of length n. |
class_probs |
An n length vector of probabilities for the proposed model. |
weight |
A n length vector of observation weight terms. This is currently designed to be either the exposure for a Poisson model or the number of trials for a Logistic model. |
tol |
The tolerance to repeat the Newton-Raphson optimization till. |
debug |
Debugging flag - set to TRUE to output step-by-step change in parameter values. |
family |
The GLM family being considered. |
maxiter |
Maximum number of NR steps to take. |
The parameter values on convergence.
1 2 3 4 5 6 | x <- model.matrix(~ factor(wool) + factor(tension), warpbreaks)
y <- warpbreaks$breaks
u <- make.dpois(x, y)
b <- c(1, 1, 1, 1)
class_probs <- rep(1, 54)
em.fit_numeric(b = b, x=x, y=y, class_probs = class_probs)
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