Let X1....,Xn be a sample of size n from a distribution with expectation u and variance sigma^2 and let u = (2X1+X2+...+Xn-1+2Xn)/(n+1) be an estimator for u. u is consistent,asymptotically unbiased ,unbiased?
Let X1....,Xn be a sample of size n from a distribution with expectation u and variance...
1. Let X1, . . . , Xn be a sample of size n from a distribution with expectation μ (2X1 + X2 + . . . + Xn-1 + 2Xn)/(n+1)l be an estimator and variance σ . and let μ- for μ. Is it unbiased? asymptotically unbiased? consistent?
1. Let X1, X2,... .Xn be a random sample of size n from a Bernoulli distribution for which p is the probability of success. We know the maximum likelihood estimator for p is p = 1 Σ_i Xi. ·Show that p is an unbiased estimator of p.
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...
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, ..., Xn be a random sample of size n from a population that can be modeled by the following probability model: axa-1 fx(x) = 0 < x < 0, a > 0 θα a) Find the probability density function of X(n) max(X1,X2, ...,Xn). b) Is X(n) an unbiased estimator for e? If not, suggest a function of X(n) that is an unbiased estimator for e.
Let X1, X2, ...,Xn be a random sample of size n from a population that can be modeled by the following probability model: axa-1 fx(x) = 0 < x < 0, a > 0 θα a) Find the probability density function of X(n) = max(X1, X2, ...,xn). b) Is X(n) an unbiased estimator for e? If not, suggest a function of X(n) that is an unbiased estimator for 0.
2. Let X1,..., Xn be i.i.d. according to a normal distribution N(u,02). (a) Get a sufficient statistic for u. Show your work. (b) Find the maximum likelihood estimator for u. (c) Show that the MLE in part (b) is an unbiased estimator for u. (d) Using Basu's theorem, prove that your MLE from before and sº, the sample variance, are independent. (Hint: use W; = X1-0 and (n-1)32)
1. Let X1, ..., Xn be a random sample of size n from a normal distribution, X; ~ N(M, 02), and define U = 21-1 X; and W = 2-1 X?. (a) Find a statistic that is a function of U and W and unbiased for the parameter 0 = 2u – 502. (b) Find a statistic that is unbiased for o? + up. (c) Let c be a constant, and define Yi = 1 if Xi < c and...
8. Let X1,...,Xn denote a random sample of size n from an exponential distribution with density function given by, 1 -x/0 -e fx(x) MSE(1). Hint: What is the (a) Show that distribution of Y/1)? nY1 is an unbiased estimator for 0 and find (b) Show that 02 = Yn is an unbiased estimator for 0 and find MSE(O2). (c) Find the efficiency of 01 relative to 02. Which estimate is "better" (i.e. more efficient)? 8. Let X1,...,Xn denote a random...
PROBLEM 3 Let X1, X2, ..., Xn be a random sample from the following distribution - 5) +1 if 0 <r <1 fx(2) = 10 0. 0.w.. where @ € (-2, 2) is an unknown parameter. We define the estimate ēn as: ô, = 12X – 6 to estimate . (a) Is ên an unbiased estimator of e? (b) Is Ôn a consistent estimator of e?