Refer to exercise 9.109{
Suppose that n integers are drawn at random and with replacement from the integers 1, 2, ..., N. That is, each sampled integer has probability of 1/N of taking on any of the values 1, 2, ..., N, and the sampled values are independent.
(a) Find the method-of-moments estimator of N.
(b) Find
}
(a) Find the MLE, of N.
Refer to exercise 9.109{ Suppose that n integers are drawn at random and with replacement from...
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
Let X1, X2, ...... Xn be a random sample of size n from EXP() distribution , , zero , elsewhere. Given, mean of distribution and variances and mgf a) Show that the mle for is . Is a consistent estimator for ? b)Show that Fisher information . Is mle of an efficiency estimator for ? why or why not? Justify your answer. c) what is the mle estimator of ? Is the mle of a consistent estimator for ? d) Is...
1. [8 points] Suppose Xi... Xn is a random sample from a Pareto distribution with the density If x > 1 otherwise, where ? > 1, Find the method of moments estimator of ?.
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).
5. Suppose that X, X, ..., X, is a random sample from a distribution with the density function (@+1)x®, if 0 < x <1 1 0, otherwise (where @ > -1 is unknown). (a) Show that the moments estimator of e is à 28-1 1-X (b) (c) (where X denotes the sample mean, as usual). Show that is a consistent estimator of e. U = - h, In X, is a sufficient statistic for 8. Is a function of U?...
5. Let X1,...,Xn be a random sample from the pdf f(\) = 6x-2 where 0 <O<< 0. (a) Find the MLE of e. You need to justify it is a local maximum. (b) Find the method of moments estimator of 0.
Let X1, . . . , Xn be a random sample from a population with density 8. Let Xi,... ,Xn be a random sample from a population with density 17 J 2.rg2 , if 0<、〈릉 0 , if otherwise ( a) Find the maximum likelihood estimator (MLE) of θ . (b) Find a sufficient statistic for θ (c) Is the above MLE a minimal sufficient statistic? Explain fully.
2. Suppose X1, X2, . .., Xn are a random sample from θ>0 0, otherwise Note: If X~fx(a; 0), thenXEx(0). (a) Find the CRLB of any unbiased estimator of θ (b) Is the MLE for θ the MVUE?
Let n be a positive integer. For each possible pair i, j of integers with 1 sisi<n, find an n x n matrix A with the property that 1 is an eigenvalue of A with g(1) = i and a(1) = j.
7. Let Y1, ...,Yn be a random sample from the population with pdf f(316) = he=1/0, y>0 (a) Find the MOM estimator for 0. (b) Find the MLE of 0. (c) Find the MLE of P(Y < 2). (d) Find the MLE of the median of the distribution.