a)
b)
MoM
E(X) =
hence
c)
MLE =3.35
MoM = (7.50 + 3.73 + 4.52 + 3.35)/8
= 2.3875
Problem 1.2 Let Xi, X2, ..., Xn be a random sample from the pdf a) Find...
2. Let Xi,..., Xn be a random sample from the pd f (a) Find the method of moments estimator of θ. (b) Find the maximum likelihood estimator of θ.
6. Let Xi,.Xn be a random sample from the pdf Find the method of moments estimator of θ.
Suppose that X1, X2,....Xn is an iid sample of size n from a Pareto pdf of the form 0-1) otherwise, where θ > 0. (a) Find θ the method of moments (MOM) estimator for θ For what values of θ does θ exist? Why? (b) Find θ, the maximum likelihood estimator (MLE) for θ. (c) Show explicitly that the MLE depends on the sufficient statistic for this Pareto family but that the MOM estimator does not
Suppose that Xi, X2,., Xn is an iid sample from (1- 0) In 0 0, X(T 0, herwise, where the parameter θ satisfies 0 θ 1. (a) Estimate θ using the method of moments (MOM) and using the method of maximum likelihood. Note: I am not sure if you can get closed form expressions for either estimator, but that is OK. Just write out the equation(s) that would need to be solved (numerically) to
Number 2 only PLEASE 1. [40] 6.4-5. Let Xi, X2..,Xn be a random sample from dis- tributions with the given probability density functions. In each case, find the maximum likelihood estimator . 6.4-10. Let X1, X2,... ,Xn be a random sample of size n from a geometric distribution for which p is the probabil- ity of success. (a) Use the method of moments to find a point estimate 2. [20] for p. 100] 6.5-3. The midterm and final exam scores...
Let X1,..., Xn be a random sample from the pdf f(x:0)-82-2, 0 < θ x < oo. (a) Find the method of moments estimator of θ. (b) Find the maxinum likelihood estimator of θ
1. Let X1, ..., Xn be a random sample from a distribution with the pdf le-x/0, x > 0, N = (0,00). (a) Find the maximum likelihood estimator of 0. (b) Find the method of moments estimator of 0. (c) Are the estimators in a) and b) unbiased? (d) What is the variance of the estimators in a) and b)? (e) Suppose the observed sample is 2.26, 0.31, 3.75, 6.92, 9.10, 7.57, 4.79, 1.41, 2.49, 0.59. Find the maximum likelihood...
Let Xi,... , Xn be a random sample from a normal random variable X with E(X) 0 and var(X)-0, i.e., X ~N(0,0) (a) What is the pdf of X? (b) Find the likelihood function, L(0), and the log-likelihood function, e(0) (c) Find the maximun likelihood estimator of θ, θ (d) Is θ unbiased?
2. Let Xi,... ,Xn be a random sample from a distribution with p.d.f for 0 < x < θ f(x; 0) - 0 elsewhere . (a) Find an estimator for θ using the method of moments. (b) Find the variance of your estimator in (a).
3. Let Xi,... , X,n be a random sample from a population with pdf 0, otherwise, where θ > 0. a) Find the method of moments estimator of θ. (b) Find the MLE θ of θ (c) Find the pdf of θ in (b).