


Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
This is the Past Exam of Generalised Linear Models which includes Values, Fixed, Integer, Expectation, Variance, Probability Mass Function, Standard Notation, Logit Functions, Logistic etc. Key important points are: Values, Fixed, Integer, Expectation, Variance, Probability Mass Function, Standard Notation, Logit Functions, Logistic, Residual Deviance
Typology: Exams
1 / 4
This page cannot be seen from the preview
Don't miss anything!



PART II (Third or Fourth Year) MATHEMATICS & STATISTICS Math 352 Generalised Linear Models 90 minutes
You should answer ALL Section A questions and ONE Section B question. In Section A there are questions worth a total of 50 marks, but the maximum mark that you can gain there is capped at 40. SECTION A
A1. Let Z ∼ Bino(m, μ), 0 < μ < 1, and fixed known integer m > 0. Define Y = Z/m so that Y ∼ Binoprop(m, μ). (a) State the values of Z (the support) which have non-zero probability. [2] (b) Find the expectation and variance Y. [4] (c) Write down the probability mass function of Y. [2] (d) Explain why Z is not a GLM in the standard notation of GLMs but that Y is. [2]
A2. Define the logistic and logit functions, and show these are inverse. [8]
A3. Define the residual deviance of a GLM in terms of the log likelihood, expressed as a function of the moment parameters, μi, and the observations, yi, i = 1, 2 ,... , n. [4] State what the deviance measures. [2]
A4. Show that the exponential family (EF) generated from the exponential pdf q(y) = 2 exp(− 2 y), y > 0, and Y may be written as f (y|θ) = 2 exp(− 2 y) exp{θy + log(1 − θ/2)} where θ < 2. [6] Identify the mean of this pdf in terms of the canonical parameter θ. [4] Find the maximum likelihood estimate of θ based on a single observation y from this pdf. [6] please turn over
SECTION A continued
A5. An experiment consists of 6 units to which the following treatment combinations are applied. 1 A 2 B 2 2 A 1 B 2 3 A 1 B 2 4 A 2 B 1 5 A 3 B 1 6 A 3 B 1 (a) Write out the matrix that corresponds to this design in terms of the indicator vectors for these factor levels. [4] (b) Define the factor A in terms of these indicator vectors. [2] (c) Write out the design matrix (the X matrix) for the model in which the linear predictor η ∈ A + B. [2] (d) Modify this matrix for the model in which the linear predictor η ∈ A + B + A.B. [2]
please turn over
SECTION B continued
B2. There are three notations for GLMs: generic, index, vector notation. (a) Explain these different notations when describing the response variable, [6] (b) The diagram of a GLM is
m
m
m m
m J m
JJ ≠≠≠
Add labels to the diagram to represent the generic concepts that go to define a GLM. [4] (c) Give brief definitions of these generic concepts. [8] (d) Add directions to the edges of this diagram to help explain the interrelationships be- tween the generic concepts of a GLM, and label the edges with GLM functions where appropriate. [4] (e) Describe these interrelationships. [8]
end of exam