Dear All,
The std. error of the estimated coefficients
obtained by the summary.lm function can be calculated
as:
y=rnorm(20)
x=y+rnorm(20)
fit <- lm(y ~ x)
summary(fit)
sqrt( sum(fit$resid**2)/fit$df.resid *
solve(t(model.matrix(fit))%*%model.matrix(fit)) )
Is posible calculate Std. Error for glm as lm, using
cov(hat beta) = phi * solve(t(X) %*% hat W %*% X)^-1
on R? Who is hat W and phi output glm?
y=rpois(20,4)
fit.glm <- glm(y ~ x, family=poisson
summary(fit.glm)
Fitted to a model glm using constrast contr.sum and need compute
the error standard for last level of the factor.
best wishes for all,
Ricardo.
Veja quais são os assuntos do momento no Yahoo! +Buscados
http://br.maisbuscados.yahoo.com
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
