Generate 300 observations from the vma1 model fit the vma1


Question: Consider the bivariate VMA(1) model

1025_Equation.png

where at is a Gaussian white noise series with mean zero and identity covariance matrix.

(a) Generate 300 observations from the VMA(1) model. Fit the VMA(1) model by both the conditional and exact likelihood methods. Write down the fitted models.

(b) To gain insight into VMA modeling, conduct a simulation study using the given VMA(1) model with sample size T = 300 and 1000 iterations. For each iteration, fit the VMA(1) model via the conditional maximum likelihood method and compute the Portmanteau statistic Q2(5) of the residuals. Store the coefficient estimate 1 and the Q2(5) statistic over the 1000 iterations. Compute the sample means, standard errors, and the 2.5th and 97.5th percentiles of each parameter estimate and the Q2(5) statistic. Compare the summary statistics with their asymptotic counterparts.

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Engineering Mathematics: Generate 300 observations from the vma1 model fit the vma1
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