Hi,
I'm programming in R and below is a summary of a generalized linear model:
************************************************** ***
Call:
glm(formula = offspring ~ degdays, family = quasi(link = "log",
variance "mu"), data = fecundity)
Deviance Residuals:
Min 1Q Median 3Q Max
-0.76674 -0.29117 -0.09664 0.15668 1.00800
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.131351 0.030480 -37.12 <2e-16 ***
degdays -0.008803 0.000299 -29.44 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
'.' 0.1 ' ' 1
(Dispersion parameter for quasi family taken to be 0.09437092)
Null deviance: 266.29 on 1674 degrees of freedom
Residual deviance: 164.54 on 1673 degrees of freedom
AIC: NA
Number of Fisher Scoring iterations: 6
************************************************** *
For my modelling purposes, I understand that my mean is
exp(-1.131351-.008803*degdays). What I want to do is to draw a random number
from a lognormal distribution with this mean. What is my variance? Is it the
dispersion parameter * mean? Or exp(dispersion parameter * mean)? Or am I
completely offbase?
Thanks.
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