Consider the binary response variable Y ~ Bernoulli with P(Y-1) π and P(Y = 0) =...
LetX,X2, , XnLLd. Bernoulli(p), and let Y-Σ,Xi. Then we know that Y-Binomial(n, p). 5. Consider the hypotheses Hop-po against HA:p#po- a. Find the likelihood function of p in terms of random variable Y, L(p). b. Construct the (generalized) likelihood ratio λ(v). Hint: what is pMLE?] C. (i) For the particular case of po 0.25 and n 5, fill in the table: 3 4 A(y) (ii) Rearrange the table in the order of increasing of values of 2, and compute cumulative...
4. Let X,X,Bernoulli(p), and let Y Xi. Then we know that Y-Binomial(n.p) Consider the hypotheses Hop-Po against Hip#po- a. c. For the particular case of po0.25 and n 5, fill in the table: 0 3 4 λ(y) P(Y - y) Find the (generalized) likelihood ratio test φ(y) of size α for testing Ho:p-po vs. H,: p d. po. Your test should be expressed in terms of y and α.
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
In order to test customer satisfaction with a given service, we conduct a survey and define a random variable Yi as follows:Yi = 1 if customer i is satisfiedYi = 0 if the customer i is not satisfiedGiven the identical and independent Bernoulli distributed samples y1, …, yn withP[Yi = 0] = θP[Yi = 1] = 1 – θwe want to test the hypotheses H0: θ = θ0 = 0:52 et H1 = θ = θ1 = 0:48• Construct the...
5.35 A study has ni independent binary observations (y yin) when Xx, Σί ni. Consider the model logit(m):: α+pm, where 1, , N, with n a. Show that the kernel of the likelihood function is the same treating the d b. For the saturated model, explain why the likelihood function is different for these c. Explain why the difference between deviances for two unsaturated models does d. Suppose that each n 1. Show that the deviance depends on fi but...
Exercise 6.14 Let y be distributed Bernoulli P(y = 1) unknown 0<p<1 p and P(y = 0) = 1-p f or Some (a) Show that p E( (b) Write down the natural moment estimator p of . (c) Find var (p) (d) Find the asymptotic distribution of vn (-p) as no. as n> OO.
Solve only ,h , i and j ,
(1) Consider a so-called Bernoulli equation: y'+p(x)y = f(x)y" where n is a real number not equal to 0 nor 1. (e) Now we try an altogether different approach to dealing with y'+p(x)y (x)y" Let yi be a non-trivial solution to y' + p(x)y = 0 (easily determined). Consider the substitution y/. Solve this for y and determine y. Put the answer in the box provided. (f) Derive a first order separable...
Consider a random sample X1, ..., Xn from a normal distribution with known mean 0 and unknown variance 0 = 02 (a) Write the likelihood and log-likelihood function (b) Derive the maximum likelihood estimator for 6 (c) Show that the Fisher information matrix is I(O) = 2014 (d) What is the variance of the maximum likelihood estimator for @? Does it attain the Cramer-Rao lower bound? (e) Suppose that you are testing 0 = 1 versus the alternative 0 #...
1. Let X1, ..., Xn be iid with PDF 1 xle f(x;0) = x>0 (a) Determine the likelihood ratio test to test Ho: 0 = 0, versus H:0700 (b) Determine Wald-type test to test Ho: 0 = 0, versus Hį:0 700 (C) Determine Rao's score statistic to test Ho: 0 = 0, versus Hų:0 700
Consider a binary erasure channel, in which the input X ∼
Bernoulli ? (1 ?,
3)
and the output Y ∈ {0, e, 1} where the symbol e denotes an
erasure event (e appears when the channel is too “bad”). The
conditional distribution of Y given X is as follows:
pY |X (0|0) = 0.9, pY |X (e|0) = 0.1, pY |X (1|1) = 0.8, pY |X
(e|1) = 0.2.
Given that an erased symbol has been observed, i.e., Y...