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please explain all steps value when p= p= p= 1, and p = h. Note that...
a) Prove that if Y is a random variable with all of its cumulants of order greater than two equal to zero, i.e., 0 = K_3 = K_4 = ......... then Y has a normal distribution. b) Suppose that Z has cumulant generating function k_Z(t) with E(Z) = 0 and Var(Z) = 1. Let Y = σZ + μ. Find the cumulant generating function of Y , k_Y (t) in terms of k_Z(.). Use this to prove that all cumulants...
pls explain to me step by step. pls write clearly and dont skip any steps. i will rate ur answer immediately. thanks. A metric space is a set M together with a distance function p(x, y) "distance" between elements a and y of the set M. The distance function must satisfy that represents the (i) f (x,y) 0 and p(z, y)--0 if and only if x y; (ii) ρ(z,y)=ρ(y,x); (iii) ρ(z, y) ρ(z, z) + ρ(z, y) for all x,...
I. The random variables X,, where P(success) = P(X = 1) = p = 1-P(X = 0) for1,2,..., represent a series of independent Bernoulli trials. Let the random variable Y be the trial number on which the first success is achieved (a) Explain why the probability mass function of Y is f(y) = pqy-1, y = 12. where q 1- p. State the distribution of Y. 2 part of your answer you should verify this is a marimum likelihood estima-...
No a,b needed. please do c and d with clear steps A mixture of m univariate Gaussians has the PDF: X(x) - where each pi 0 and Σ-i pi-1, and N(x; μ, σ*) = (2πσ2)-1/2 exp (-(x-p?/(2σ2)) exp (-(x-μ)2 a) How many parameters does a mixture of m Gaussians have? b) Let xi, , Vn be n observations drawn from a mixture of m Gaussians. Write down the log-likelihood function. Hint: it should involve two summations c) Let 1 k...
he second form for one-parameter exponential family distributions, introduced during lecture 09.1, was Jy (y | θ) = b(y)ec(0)t(y)-d(0) Let η = c(0). If c is an invertible function, we can rewrite (1) as where η is called the natural, or canonical, parameter and K(n) = d(C-1(n)). Expression (2) is referred to as the canonical representation of the exponential family distribution (a) Function κ(η) is called the log-normalizer: it ensures that the distribution fy(y n) integrates to one. Show that,...
please work out parts b,c,d with clear steps thanks A mixture of m univariate Gaussians has the PDF: X(x) - where each pi 0 and Σ-i pi-1, and N(x; μ, σ*) = (2πσ2)-1/2 exp (-(x-p?/(2σ2)) exp (-(x-μ)2 a) How many parameters does a mixture of m Gaussians have? b) Let xi, , Vn be n observations drawn from a mixture of m Gaussians. Write down the log-likelihood function. Hint: it should involve two summations c) Let 1 k < m....
I need help with this problem. Please explain in detail. 7. (based on 3.3.9) Let X have a Gamma distribution with parameters a and B. Show that Hint: It may be helpful to use the following bound from last term's homework (you do not need to reprove this bound): If X has mgf M(t), then for any a and for any t where the mgf is defined we have P(X 2 a) < eaM(t)
Please prove the following theorem: Let Yı, Y2, ... ,Yn be independent normally distributed random variables with E(Y;) = Hi and V(Y) = 0;, for i = 1, 2,..., n, and let 21, 22, ...,an be constants. If maiYi = ajY1 + a2Y2 + ...anYn i=1 then U is a normally distributed random variable with E(U) = Žar, and v(u) = 4:07. i= 1 (Hint: the moment generating function of Y ~ N(u,02) is 02t2 m(t) = E(etY) = exp...
12. let Mx(1) be the moment generating function of X. Show that (a) Mex+o(t) = eMx(at). (b) TX - Normal(), o?) and moment generating function of X is Mx (0) - to'p. Show that the random variable 2 - Normal(0,1) 13. IX. X X . are mutually independent normal random variables with means t o ... and variances o, o,...,0, then prove that X NOEL ?). 14. If Mx(1) be the moment generating function of X. Show that (a) log(Mx...
Name: Show all work for each problem: include relevant steps and explain all answers. Answers should be clearly labeled. Problem 1 Prove that the v2 is irrational. Note that you must also prove the following corollary: If the square of a number is even, then the number itself is even. Use the definition below to assist you: Definition: We say that a real number r is rational if there exist integers p and such that , where is not equal...