Answer:
Given Data
Given pdf of Y is
Likelihood function is
Taking log on both sides ,
Log likelihood of function is
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Problem 4 Let Yı, Y2, ..., Y, denote a random sample from the probability density function...
(1 point) Let Yı, Y2, ..., Yn be a random sample from the probability density function f(yla) = |aya-2/5° f(y ) 0 <y< 5 otherwise 0 for > -1. Find an estimator for a using the method of moments.
Let Yı, Y, have the joint density S 2, 0 < y2 <yi <1 f(y1, y2) = 0, elsewhere. Use the method of transformation to derive the joint density function for U1 = Y/Y2,U2 = Y2, and then derive the marginal density of U1.
The Rayleigh density function is given by 2y) -y2 е ө y >0 f(y) = --{@ elsewhere The quantity Y? has an exponential distribution with mean o. If Yı, Y2, ..., Yn denotes a random sample from a Rayleigh distribution, show that Wn = ?=1 Y/? is a consistent estimator for e.
Let Yı, ..., Yn be an independent and identically distribution sample from the distribution function f(y) = 3y?, for 0 Sy <1. (a) Show the sample mean, y converges in probability to some constant, c. Find c. (b) Find a function that converges in probability to log(C).
Let Yı, Y2, ...,Yn be an iid sample from a population distribution described by the pdf fy(y|0) = (@+ 1) yº, o<y<1 for 0> - -1. (a) Find the MOM estimator of 0. (b) Find the maximum likelihood estimator (MLE) of 0. (c) Find the MLE of the population mean E(Y) = 0 +1 0 + 2 You do not need to prove that the above is true. Just find its MLE.
1. Let X and Y be random variables with joint probability density function flora)-S 1 (2 - xy) for 0 < x < 1, and 0 <y <1 elsewhere Find the conditional probability P(x > ]\Y < ).
Problem 5 Let Y1 denote the minimum of a random sample of size n from a distribution that has pdf f(x) e(,0x< o0, zero elsewhere X- n (Y1 0), find the cumulative distribution function (cdf) for Zn = n (Y1 - 0), and Let Zn find the limiting cdf of Zn as n >oo.
2. Let Xi, X2, . Xn be a random sample from a distribution with the probability density function f(x; θ-829-1, 0 < x < 1,0 < θ < oo. Find the MLE θ
Let X and Y be two continuous random variables having the joint probability density 24xy, for 0 < x < 1,0<p<1.0<x+y<1 0, elsewhere Find the joint probability density of Z X + Y and W-2Y.
1. a) Let X and Y be random variables with the following joint probability density function (pdf) Зу f(x,y) = 0<y< 2x2,0<x< 1. 2.02 i) Obtain the value for E(Y|X = }). ii) Show the relationship between E[Y|X] and E[XY]. Use this result to obtain E[XY]