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2. Suppose you decide to randomly generate numbers from X ~ Unif (0,0). Your friend will ask for n numbers and then use this information to guess what value you (secretly) chose for θ. Typically, one might use θMLE-max Xi-X, to estimate θ. Your friend, however, has meganumerophobia, and is afraid to say the maximum number in the random sample. Instead hell say the second largest number: θ-Xn-1. Determine the bias of this estimator by carefully finding the density function for X-1 and continuing from there. If the estimator is biased, check if it is asymptotically unbiased, and also modify it to create a new unbiased estimator

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2 Xn-1) is he 2nd La rmge st mum ber sharishie Cn-n-1) n-n+ 0 o.w. , wheve Fythe cdf of x and fx (%) is the pdf of X random sample of size n from a populahion wi edf F x) a nd pdf fx (x), khen the pdf of rhe m 1 o.w . The pdf of X isThe edf of乂is (X.) (x)-n (n-2) .w M 2 0 Now χ.vn 1 n-1/X. (θ-X n(n-リ0 n(V)-リ m+1 n(n-1 ) θ mn-I nintl) (M-1) n+ Bias of he estimatoX n-)is biased (M-1) asymtohically unbiased, ,s の. Syvn un biase n-1) n- unbiased eshimatoY is nt n-I

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