13.7.3 A simple model (in degrees Cel- sius) for the daily temperature process O(t) of Example 13.3 is +4Xn, = 16 |1 - COS 365 72 where X1, X2,... is an iid random sequence of Gaussian (0, 1) random variables. (a) What is E[C,? (b) Find t he aut ocovariance funct ion Cclm.k. (c) Why is this model overly simple?

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Probability and Stochastic Process
Hint: E[W]=1 and E(W =2.
(See
13.7.3 A simple model (in degrees Cel-
the sius) for the daily temperature process C(t)
of Example 13.3 is
mpany
n pro-
at the
Lime t
eight
of the
et ween
Cn = 16 1 -
+4X,,
- COS
725
365
where X1, X2,... is an iid random sequence
of Gaussian (0, 1) random variables.
(a) What is E[Cn]?
ces) is
notion
(b) Find
t he
aut ocovariance
funct ion
Cc(m, k).
(c) Why is this model overly simple?
n (0,1)
nce Y,
13.7.4 Adifferctmedel rthe daily
Transcribed Image Text:Hint: E[W]=1 and E(W =2. (See 13.7.3 A simple model (in degrees Cel- the sius) for the daily temperature process C(t) of Example 13.3 is mpany n pro- at the Lime t eight of the et ween Cn = 16 1 - +4X,, - COS 725 365 where X1, X2,... is an iid random sequence of Gaussian (0, 1) random variables. (a) What is E[Cn]? ces) is notion (b) Find t he aut ocovariance funct ion Cc(m, k). (c) Why is this model overly simple? n (0,1) nce Y, 13.7.4 Adifferctmedel rthe daily
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