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EMET3007/8012 - Week 2 Tutorial
发布时间:2022-09-27
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EMET3007/8012 - Week 2 Tutorial
1. Modelling Cyclical Components
We described a sinusoidal cyclical component of a model as
ct = b1 sin(ωt) + b2 cos(ωt)
We want to justify using this functional form for the cyclical component.
a) Show, by giving an example, that there exist sinusoidal cycles which cannot be written as b sin(ωt).
b) Show that any sinusoidal cycle which can be written as t = b sin(θt + k) can also be written as b1 sin(ωt) + b2 cos(ωt).
c) Argue why we might prefer to use the original formulation rather than the new formulation given in (b).
2. Covariance
Let a, b e R and X, Y be random variables. Show that
a) Cov(X, Y) = E(XY) - E(X )E(Y)
b) Var(aX + b) = a2Var(X )
c) Var(X + Y) = Var(X ) + 2Cov(X, Y) + Var(Y)
d) Compare these results to the equivalent results for the expectation operator.
3. Covariance Matrix
Let X be a random vector. Show that:
Σ = E[(X - ux )(X - ux )\]
4. Affine Transformations of Multi-Variate Normals
Let X be an n-dimensional multi-variate normal distribution with X ~ N(0, In ). Let Y = u + CX for some vector u e Rn and some n × n matrix C .
a) Describe the random vector X.
b) Show that Y ~ N(u, CC\ )
c) Compare this to the single-variable case discussed in lecture.
5. Adding Up Random Variables
Let X1 , X2 , X3 be independent identically distributed random variables with Xi ~ N(1, 3). Let Y1 = X1 + X2 + X3 , Y2 = 2X1 - X2 , and Y = (Y1 , Y2 )\
a) What is the expected value of Y?
b) What is the covariance matrix of Y?
c) What is the distribution of Y?