Let x ∈ r n×p be a n × p matrix and y ∈ r n . the gaussian linear model with known variance σ 2 > 0 is defined as p = {normaln(xθ, σ2 in) | θ ∈ r p } , where normaln denotes the n-variate gaussian distribution. (a) prove that θ is identifiable if and only if x has full column rank

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