I am using data which include a (sample-)weight for each observation, i.e. the data is from a survey that has weights to make the sample representative for the US-population. I perform OLS to get some coefficients and I am trying to estimate the error variance...
I have an overdispersion problem in my model.. I have the following data:
y= succes/fail (%)
x= Var1 : Temperature data
m1<-glm(cbind(succes,fail)~Var1, data=data, family = binomial(logit))
glm(formula = cbind(succes, fail) ~ Var1, family = binomial(logit),
data = data)...
I'm generating a random normal distribution and i don't control the mu and sigma (its a matlab function that i need to use because the ratio between the numbers). Is there any way to change the mu and sigma and still keep the same ratio between the numbers in the vector?
I hope you...
This appears to be the only difference between a sigma-algebra and a Dynkin system:
Sigma-algebra is closed under countable union
Dynkin system is closed under countable union of disjoint sets
This seems to result in the D-system not being a pi-system (while the sigma-alg is). Why...