Question on time series/cauchy distribution

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Homework Help Overview

The discussion revolves around the transformation of a time series represented by two different mathematical forms. The original poster presents Form 1, which involves a cosine function with a uniform random variable, and Form 2, which incorporates independent identically distributed normal variables. The goal is to determine if Form 2 can be expressed similarly to Form 1.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the relationship between the two forms and question how to express Form 2 in a manner akin to Form 1. There is a hint regarding the distribution of a ratio of normal variables leading to a Cauchy distribution, prompting inquiries about the implications of this relationship.

Discussion Status

Some participants have offered hints regarding the use of trigonometric identities to facilitate the transformation between the two forms. There is an acknowledgment of the original poster's confusion, and the discussion is ongoing with attempts to clarify the mathematical connections.

Contextual Notes

The original poster expresses uncertainty about the steps needed to approach the problem, indicating a potential lack of familiarity with the relevant mathematical concepts and identities.

caspian2012
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1. (Form 1) X_t = A cos(λt +φ ) ,
where φ was Unif [−pi ,pi ] , λ is a fixed constant and A is a constant (or a RV mean 0,
variance \σ^\2_\A, and indep of φ ). ]
Now consider the following: Let B_1 , B_2 be IID Normal(0,\σ^\2_\B) and λ a fixed constant
(Form 2) Y_t = B_1 cos(λ_t) + B2 sin(λ_t)
Can Form 2 be written in a manner similar to Form 1? If so, show how.
[Hint: you know the distribution of {\frac{\-B_2}{B_1}}
(Cauchy). Define
φ = arctan({\frac{\-B_2}{B_1}}) . What is the distribution of φ ?]


I am lost in what I need to do. Could someone give me some help? Or some hint?

Thanks!
 
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This is my first post so I guess I will try to type everything again. Hopefully it works this time.
 
1. (Form 1) [tex]X_t[/tex]= A cos(λt +φ ) ,
where φ was Unif [−pi ,pi ] , λ is a fixed constant and A is a constant (or a RV mean 0,
variance [tex]\σ^\2_\A[/tex], and indep of φ ). ]
Now consider the following: Let [tex]B_1[/tex] , [tex]B_2[/tex]be IID Normal(0,[tex]\σ^\2_\B[/tex]) and λ a fixed constant
(Form 2) [tex]Y_t[/tex] = [tex]B_1[/tex] cos([tex]λ_t[/tex]) + B2 sin([tex]λ_t[/tex])
Can Form 2 be written in a manner similar to Form 1? If so, show how.
[Hint: you know the distribution of [tex]{\frac{\-B_2}{B_1}}[/tex]
(Cauchy). Define
φ = arctan([tex]{\frac{\-B_2}{B_1}}[/tex]) . What is the distribution of φ ?]
 
caspian2012 said:
1. (Form 1) X_t = A cos(λt +φ ) ,
where φ was Unif [−pi ,pi ] , λ is a fixed constant and A is a constant (or a RV mean 0,
variance \σ^\2_\A, and indep of φ ). ]
Now consider the following: Let B_1 , B_2 be IID Normal(0,\σ^\2_\B) and λ a fixed constant
(Form 2) Y_t = B_1 cos(λ_t) + B2 sin(λ_t)
Can Form 2 be written in a manner similar to Form 1? If so, show how.
[Hint: you know the distribution of {\frac{\-B_2}{B_1}}
(Cauchy). Define
φ = arctan({\frac{\-B_2}{B_1}}) . What is the distribution of φ ?]


I am lost in what I need to do. Could someone give me some help? Or some hint?

Thanks!

Just use standard trigonometric identities; in particular, how can you write sin(a+b) in terms of sin(a), sin(b), cos(a) and cos(b)?

RGV
 
Ray Vickson said:
Just use standard trigonometric identities; in particular, how can you write sin(a+b) in terms of sin(a), sin(b), cos(a) and cos(b)?

RGV

Thanks. I thought it would be much more tricky, guess not.
 

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