(i) Suppose that Y1,…,Yn are independent random variables, and that Yi has probability density function
f(yi∣θi,ϕ)=exp[(yiθi−b(θi))/ϕ+c(yi,ϕ)]
Assume that E(Yi)=μi, and that g(μi)=βTxi, where g(⋅) is a known 'link' function, x1,…,xn are known covariates, and β is an unknown vector. Show that
E(Yi)=b′(θi),var(Yi)=ϕb′′(θi)=Vi, say,
and hence
∂β∂l=i=1∑ng′(μi)Vi(yi−μi)xi, where l=l(β,ϕ) is the log-likelihood.
(ii) The table below shows the number of train miles (in millions) and the number of collisions involving British Rail passenger trains between 1970 and 1984 . Give a detailed interpretation of the R output that is shown under this table:
1234567891011121314 year 19701971197219731974197519761977197819791980198119821983 collisions 36476224173561 miles 281276268269281271265264267265267260231249
Call:
glm(formula = collisions ∼ year +log( miles ), family = poisson)
Coefficients:
(Intercept) year log (miles) Estimate 127.14453−0.05398−3.41654 Std. Error 121.377960.051754.18616 z value 1.048−1.043−0.816Pr(>∣z∣)0.2950.2970.414
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 15.937 on 13 degrees of freedom
Residual deviance: 14.843 on 11 degrees of freedom
Number of Fisher Scoring iterations: 4
Part II