Let xt be a gaussian process with mean microxnbspt and


Let X(t) be a Gaussian process with mean µX (t) and autocovariance CX(t,τ). In this problem, we verify that the for two samples X(t1), X(t2), the multivariate Gaussian density reduces to the bivariate Gaussian PDF. In the following steps, let σ2i denote the variance of X(ti) and let ρ = CX (t1,t2 - t1)/(σ1σ2) equal the correlation coefficient of X(t1) and X(t2).

(a) Find the covariance matrix C and show that the determinant is

(b) Show that the inverse of the correlation matrix is

(c) Now show that the multivariate Gaussian density for X(t1), X(t2) is the bivariate Gaussian density.

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Basic Statistics: Let xt be a gaussian process with mean microxnbspt and
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