fipois.reg: Fixed intercepts Poisson regression

In Rfast2: A Collection of Efficient and Extremely Fast R Functions II

Fixed intercepts Poisson regression

Description

Fixed intercepts Poisson regression.

Usage

fipois.reg(y, x, id, tol = 1e-07, maxiters = 100)

Arguments

y	The dependent variable, a numerical vector with integer, non negative valued data.
x	A matrix with the indendent variables.
id	A numerical variable with 1, 2, ... indicating the subject. Unbalanced design is of course welcome.
tol	The tolerance value to terminate the Newton-Raphson algorithm. This is set to 10^{-7} by default.
maxiters	The maximum number of iterations that can take place during the fitting.

Details

Fixed intercepts Poisson regression for clustered count data is fitted. According to Demidenko (2013), when the number of clusters (N) is small and the number of observations per cluster (n_i) is relatively large, say min(n_i) > N, one may assume that the intercept \alpha_i = \beta + u_i is fixed and unknown (i=1,...,N).

Value

A list including:

be	The regression coefficients.
seb	The standard errors of the regression coefficients.
ai	The estimated fixed intercepts fore ach cluster of observations.
covbeta	The covariance matrix of the regression coefficients.
loglik	The maximised log-likelihood value.
iters	The number of iteration the Newton-Raphson required.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

Eugene Demidenko (2013). Mixed Models: Theory and Applications with R, pages 388-389, 2nd Edition. New Jersey: Wiley & Sons (excellent book).

See Also

cluster.lm, fe.lmfit, gee.reg, covar, welch.tests

Examples

y <- rpois(200, 10)
id <- sample(1:10, 200, replace = TRUE)
x <- rpois(200, 10)
fipois.reg(y, x, id)

Rfast2 documentation built on May 29, 2024, 8:45 a.m.