AMS 268 Advanced Bayesian
نویسنده
چکیده
Let x = (x1, . . . , xp) ′ ∼ N(0,Σ), where Σ is a p×p positive definite matrix. Assume that we have observed a sample of size n, (yi,xi) n i=1 and assume σ = 1. Consider simulating data by taking various combinations of (n, p,Σ,β) as follows: (a) n = 50, 500 (b) p = 100, 1000 (c) Σ = I,S0.1,S0.6 (d) casse (i) β1 = · · · = β5 = 3, βj = 0 for any other j; case (ii) β1 = · · · = β5 = 5, β6 = · · · = β10 = −2, β11 = · · · = β15 = 0.5, βj = 0 for any other j; case (iii) βj = 1 for all j, where Sρ,ii = 1,Sρ,ij = ρ |i−j| for i 6= j. Altogether they give rise to 36 different combinations.
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