On Sat, 2010-09-11 at 14:41 -0700, Peng, C wrote:
Is this something you want to have (based on a simulated dataset)?
counts - c(18,17,15,20,10,20,25,13,12)
#risk - round(rexp(9,0.5),3)
risk- c(2.242, 0.113, 1.480, 0.913, 5.795, 0.170, 0.846, 5.240, 0.648)
gm - glm(counts ~ risk,
Dear all,
I have a quasipoisson glm for which I need confidence bands in a graphic:
gm6 - glm(num_leaves ~ b_dist_min_new, family = quasipoisson, data = beva)
summary(gm6)
library('VIM')
b_dist_min_new - as.numeric(prepare(beva$dist_min, scaling=classical,
transformation=logarithm)).
My
On Sep 11, 2010, at 3:15 PM, Maik Rehnus wrote:
Dear all,
I have a quasipoisson glm for which I need confidence bands in a
graphic:
gm6 - glm(num_leaves ~ b_dist_min_new, family = quasipoisson, data
= beva)
summary(gm6)
library('VIM')
b_dist_min_new -
Is this something you want to have (based on a simulated dataset)?
counts - c(18,17,15,20,10,20,25,13,12)
#risk - round(rexp(9,0.5),3)
risk- c(2.242, 0.113, 1.480, 0.913, 5.795, 0.170, 0.846, 5.240, 0.648)
gm - glm(counts ~ risk, family=quasipoisson)
summary(gm)
new.risk=seq(min(risk),
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