Considere o processo Auto-Regressivo de 1ª ordem -AR(1) Consider the 1st order Auto-Regressive process -AR(1) u_t=pu_(t-1)+e_t Onde p=0.5 é uma constante e é uma variável aleatória de espetro branco e de variância igual a um. Frequentemente designa-se por inovação do período. Where p=0.5 is a constant and e_t is a random variable with a white spectrum and variance equal to one. It is often referred to as period t innovation. E(ε_t)=0,vt Var(e_t)=1 Cov(e_t,e_(t-1))=0,vt, s, #0 Calulate Cov(u_t,u_(t-3)) Resposta:

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Considere o processo Auto-Regressivo de 1ª ordem -AR(1)
Consider the 1st order Auto-Regressive process -AR(1)
u_t=pu_(t-1)+e_t
Onde p=0.5 é uma constante e é uma variável aleatória de espetro branco e de variância igual a um. Frequentemente designa-se por
inovação do período.
Where p=0.5 is a constant and e_t is a random variable with a white spectrum and variance equal to one. It is often referred to as period t
innovation.
E(ε_t)=0,vt
Var(ε_t)=1
Cov(e_t,&_(t-1) )=0,vt, s, s#0
Calulate Cov(u_t,u_(t-3))
Resposta:
Transcribed Image Text:Considere o processo Auto-Regressivo de 1ª ordem -AR(1) Consider the 1st order Auto-Regressive process -AR(1) u_t=pu_(t-1)+e_t Onde p=0.5 é uma constante e é uma variável aleatória de espetro branco e de variância igual a um. Frequentemente designa-se por inovação do período. Where p=0.5 is a constant and e_t is a random variable with a white spectrum and variance equal to one. It is often referred to as period t innovation. E(ε_t)=0,vt Var(ε_t)=1 Cov(e_t,&_(t-1) )=0,vt, s, s#0 Calulate Cov(u_t,u_(t-3)) Resposta:
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