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Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = (1/θ)e^(−x/θ) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ. Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = θe^(−θx) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ.
Let X1 Xn be a random sample of size n from a Bernoulli population with parameter p. Show that p= X is the UMVUE for p. 5.4.22 Let X1 Xn be a random sample of size n from a Bernoulli population with parameter p. Show that p= X is the UMVUE for p. 5.4.22
Let X1,... , Xn be a random sample from the Pareto distribution with pdf Ox (0+1), x > 1, f(z0) where 0>0 is unknown (a) Find a confidence interval for 0 with confidence coefficient 1-a by pivoting a ran- dom variable based on T = T log Xi. (Use quantiles of chi-square distributions to express the confidence interval and use equal-tail confidence interval (b) Find a confidence interval for 0 with confidence coefficient 1 - a by pivoting the cdf...
Let X1, . . . , Xn be a random sample from a normal distribution, Xi ∼ N(µ, σ^2 ). Find the UMVUE of σ ^2 .
Let X1,... , Xn be a random sample from the Pareto distribution with pdf { f (r0)= 0, where 0>0 is unknown (a) Find a uniformly most powerful (UMP) test of size a for testing Ho 0< 0 versus where 0o>0 is a fixed real number. (Use quantiles of chi-square distributions to express the test) (b) Find a confidence interval for 0 with confidence coefficient 1-a by pivoting a ran- dom variable based on T = log Xi. (Use quantiles...
Let X1, . . . , Xn be a random sample from a normal distribution, Xi ∼ N(µ, σ^2 ). Find the UMVUE of σ ^2 .
Let X1, X2, ...,Xn denote a random sample of size n from a Pareto distribution. X(1) = min(X1, X2, ..., Xn) has the cumulative distribution function given by: αη 1 - ( r> B X F(x) = . x <B 0 Show that X(1) is a consistent estimator of ß.
6. Let X1,..., Xn be a random sample from Uniform (0, 1). a) Find the exact distribution of U = – log(X(1)) where X(1) = min(X1, X2,..., Xn). b) Find the limiting distribution of n(1 – X(n)), where X(n) = max(X1, X2, ..., Xn).
6.1.10. Let X1, X2..... Xn be a random sample from a N(0,0%) distribution, where o? is fixed but-X <O<O. (a) Show that the mle ofis X. (b) If is restricted by 0 < < oc, show that the mie of 8 is 8 = max{0,X}.
Let X1,... , Xn be a random sample from a population with pdf 3x2/03,E(0, 0), f(x|0) = otherwise 0, where 0 >0 is unknown (a) Find a 1-a confidence interval for 0 by pivoting the cdf of X(n) = max{X1, ... , Xn}. (b) Show that the confidence interval in (a) can also be obtained using a pivotal quantity Let X1,... , Xn be a random sample from a population with pdf 3x2/03,E(0, 0), f(x|0) = otherwise 0, where 0...