here MLE is not unbiased for
p, but the function which i provided is unbiased for p and can be
proved by similar fact that sum of iid geometric follow negative
binomial distribution.. please don't dislike the answer. if you
have any doubt please ask by comment i will respond to you as soon
as will be possible. thanks....
8. (8 points) Let X1, X2, . . . , X, bea random sample from the geometric distribution with pmf f(aip) (1-P)-p,z1,2,3,..., where 0 <ps 1. Find the maximam likel ihood estimator of p and show t...
Let X1, X2, .. , Xn be a random sample of size n from a geometric distribution with pmf =0.75 . 0.25z-1, f(x) X-1.2.3. ) Let Zn 3 n n-2ућ. Find Mz, (t), the mgf of Žn. Then find the limiting mgf limn→oo MZm (t). What is the limiting distribution of Z,'?
Let X1, X2, .. , Xn be a random sample of size n from a geometric distribution with pmf =0.75 . 0.25z-1, f(x) X-1.2.3.
) Let Zn 3...
estimator of 3. (14 points each) Let X1, X2,..., X, be a random sample from Gammala, 1) distribution where a is known, and is unknown. (i) Find the moment estimator of X. (ii) Find the MLE of i noints each Let X1, X ., X, be a sample from N(u,0%).
Let > 0 and let X1, X2, ..., Xn be a random sample from the distribution with the probability density function f(x; 1) = 212x3 e-tz, x > 0. a. Find E(XK), where k > -4. Enter a formula below. Use * for multiplication, / for divison, ^ for power, lam for 1, Gamma for the function, and pi for the mathematical constant i. For example, lam^k*Gamma(k/2)/pi means ik r(k/2)/n. Hint 1: Consider u = 1x2 or u = x2....
Let > 0 and let X1, X2, ..., Xn be a random sample from the distribution with the probability density function f(x; 1) = 212x3e-dız?, x > 0. a. Find E(X), where k > -4. Enter a formula below. Use * for multiplication, / for divison, ^ for power, lam for \, Gamma for the function, and pi for the mathematical constant 11. For example, lam^k*Gamma(k/2)/pi means ik r(k/2)/ I. Hint 1: Consider u = 1x2 or u = x2....
Let X1, X2, ..., Xn be a random sample from a Gamma( a , ) distribution. That is, f(x;a,0) = loga xa-le-210, 0 < x <co, a>0,0 > 0. Suppose a is known. a. Obtain a method of moments estimator of 0, 0. b. Obtain the maximum likelihood estimator of 0, 0. c. Is O an unbiased estimator for 0 ? Justify your answer. "Hint": E(X) = p. d. Find Var(ë). "Hint": Var(X) = o/n. e. Find MSE(Ô).
Let X1,X2,...,Xn denote a random sample from the Rayleigh distribution given by f(x) = (2x θ)e−x2 θ x > 0; 0, elsewhere with unknown parameter θ > 0. (A) Find the maximum likelihood estimator ˆ θ of θ. (B) If we observer the values x1 = 0.5, x2 = 1.3, and x3 = 1.7, find the maximum likelihood estimate of θ.
2.a. Let X1, X2, ..., X., be a random sample from a distribution with p.d.f. (39) f( 0) = (1 - 1) if 0 < x <1 elsewhere ( 1 2.) = where 8 > 0. Find a sufficient statistic for 0. Justify your answer! Hint: (2(1-)). b. Let X1, X2,..., X, be a random sample from a distribution with p.d.f. (1:0) = 22/ if 0 < I< elsewhere where 8 >0. Find a sufficient statistic for 8. Justify your...
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.
Let X1,X2,,X be a random sample from a distribution function f(x,8) = θ"(1-8)1-r for x = 0,1 (a) Show that Y = Σ.1X, is a sufficient statistic for θ. (i) Find a function of Y that is an unbiased estimate for θ (ii) Hence, explain why this function is the minimum variance unbiased estimator(MVUE) for θ (c) Is1-the MVUE for Please explain.
1. Let X1, X2,...,x. be a random sample from the unif(0,0) distribution (a) Find an unbiased estimatior of O based on the sample mean X (b) Find an unbiased estimator of based on the sample maximum X (c) Which estimator is better in terms of variance?