Could I grab some help on problem 2? Thank you
Could I grab some help on problem 2? Thank you 2. Suppose Yi, Yn are iid...
2. Suppose i, ơ2. Let Y are iid normal random variables with nornnal distribution with unknown mean and variance, μ and is: 1 . For this problem you may not assume that n is large. n (a) What is the distribution of Y? (b) What is the distribution of z-(ga), (n-e), (y, e)2? (c) What is the distribution of (a- (d) What is the distribution ofw)? Justify your answer. (e) Let Zi (y e) 2 (3 ) 2 + (y...
2. Suppose Yi,.. narei normal random variables with normal distribution with unknown mean and variance, μ and or. Let Y-욤 Σ;..x. For this problem, you may not assume that n is large. (a) What is the distribution of Y? (b) what is the distribution of z-(yo), (en, (n-) (c) what is the distribution of (n-p? (d) What is the distribution of Justify your answer. (e) Let Zi-(ga)' + (-)' + (yo)", z2 = (속)' + (n-e)' what is the distribution...
4. Suppose Yi, Yn are iid randonn variables with E(X) = μ, Var(y)-σ2 < oo. For large n, find the approximate distribution of p = n Σηι Yi, Be sure to name any theorems you used.
1. Suppose Yi,½, , Yn is an iid sample from a Bernoulli(p) population distribution, where 0< p<1 is unknown. The population pmf is py(ulp) otherwise 0, (a) Prove that Y is the maximum likelihood estimator of p. (b) Find the maximum likelihood estimator of T(p)-loglp/(1 - p)], the log-odds of p. 1. Suppose Yi,½, , Yn is an iid sample from a Bernoulli(p) population distribution, where 0
4. Let Yi, ½, . . . , Yn be a random sample from some pdf/pmf f(y; θ)·Let W be a point estimator h(y, Y2, . . . , Yn) for θ. The bias of W as a point estimator for θ is defined as W Blase(W) = E(W)- The mean square error of W is defined as MSEe(W) = E(W-0)2 (a) Using properties of expected values, and the definition of variance from PSTAT 120A/B, show that MSEe(W) = Vare(W)...
4 and 5 samples, the other in small samples. Which is which? Explain. (d) Suppose we know that the 5 values are from a symmetric distribution. Then the sample median is also unbiased and consistent for the population mean. The sample mean has lower variance. Would you prefer to use the sample 4. Suppose Yi, Y, are iid r ables with E(n)-μ, Var(K)-σ2 < oo. For large n, find the approximate 5. Suppose we observe Yi...Yn from a normal distribution...
Problem 4.12 & Problem 4.14 ? 4.12 Suppose y is N4(u, 2), where 8 9 -3 6 3-3 23 μ= PROBLEMS 107 (a) Find the distribution ofz-: 4y1-2y2 + y3-3y4 (b) Find the joint distribution of zy y2y3y4 and z22yi + (c) Find the joint distribution of zı = 3y1 +N2-4y3-N4, z2--yı-3y2+ (d) What is the distribution of y3? (e) What is the joint distribution of y2 and y4? (f) Find the joint distribution of yi, 1(yi + y2), yit...
3. Let Xi, . . . , Xn be iid randoln variables with mean μ and variance σ2. Let, X denote the sample mean and V-Σ, (X,-X)2. (a) Derive the expected values of X and V. (b) Further suppose that Xi,-.,X, are normally distributed. Let Anxn ((a)) an orthogonal matrix whose first rOw 1S be , ..*) and iet Y = AX, where Y (Yİ, ,%), ard X-(XI, , X.), are (column) vectors. (It is not necessary to know aij...
QUESTION 5 Suppose that Yı, Y2,.., Yn independent variables such that where β is an unknown parameter, X1, x2-.., xn are known real numbers, and el,e2 independent random errors each with a normal distribution with mean 0 and variance ơ2 ,en are (a) Show that is an unbiased estimator of β. What is the variance of the estimator? (b) Given that the probability density function of Y is elsewhere, show that the maximum likelihood estimator of β is not the...
1) Consider n data points with 3 covariates and observations {xil, Гіг, xī,3, yi); i-1,.,n, and you fit the following model, y Bo+B+B32+Br+e that is yi-An + ßiXiut Ali,2 + Asri,3 + Ei where є,'s are independent normal distribution with mean zero and variance ơ2 For a observed covariate vector-(1, ri, ^2, r3) (with the intercept and three regressor variables) and observed yg at that point a) write the expression for estimated variance for the fit zs at z. (Let...