Question 7 /10 points Grads only NaiveBayes + Conditional Likelihood As you recall, the parameter...
Please give detailed steps. Thank you. 5. Let {X, : i-1..n^ denote a random sample of size n from a population described by a random varaible X following a Poisson(θ) distribution with PDF given by θ and var(X) θ (i.e. you do not You may take it as given that E(X) need to show these) a. Recall that an estimator is efficient, if it satisfies 2 conditions: 2) it achieves the Cramer-Rao Lower Bound (CLRB) for unbiased estimators: Show that...
1. Suppose that y E R is a parameter, and {X1, X2, ..., Xm} is a set of positive i.i.d. random variables with density function fx, given by fx.(ar)yey, You observe that X = {X1, X2, ..., Xm} in fact take the values r = {r1, x2, ..., x'm}, respec- tively. Write for the average of the values {x1, x2,.., Tm) a) What is the likelihood function, L(y; x), as a function of y? What is the log-likelihood function, log...
Return to the original model. We now introduce a Poisson intensity parameter X for every time point and denote the parameter () that gives the canonical exponential family representation as above by θ, . We choose to employ a linear model connecting the time points t with the canonical parameter of the Poisson distribution above, i.e., n other words, we choose a generalized linear model with Poisson distribution and its canonical link function. That also means that conditioned on t,...
In this problem, we will model the likelihood of a particular client of a financial firm defaulting on his or her loans based on previous transactions. There are only two outcomes, "Yes" or "No", depending on whether the client eventually defaults or not. It is believed that the client's current balance is a good predictor for this outcome, so that the more money is spent without paying, the more likely it is for that person to default. For each x,...
Really short question! Please help me to solve, thank you! (10%)Q3 (Logistic regression): We collected n 15 independent binary observations : i- 1, , 15) and their corresponding covariates {xi : і = 1, , 15). Assume the relationship between yi and zi (for i = 1, , 15) is Vi ~ Bernoulli(p.) and logit(Pi)-α+82i, where logit(t) = log ti. Please 1) write down the likelihood function L(a, B|x, y) of the logistic regression model; 2) derive the Newton method...
Question 2 a. Show that, for the exponential model with gamma prior, the posterior Π(9121m) under n observations can be computed as the posterior given a single observation xn using the prior q(の는 1101r1:n-1). Give the formula for the parameters (an,ßn) of the posterior ll(θ|X1:n, α0,Ao) as a function of (an-1, Bn-1). b. Visualize the gradual change of shape of the posterior II(01:n, ao, Bo) with increasing n: . Generate n 256 exponentially distributed samples with parameter θ-1. . Use...
2. Consider a simple linear regression i ion model for a response variable Y, a single predictor variable ,i1.., n, and having Gaussian (i.e. normally distributed) errors: This model is often called "regression through the origin" since E(X) = 0 if xi = 0 (a) Write down the likelihood function for the parameters β and σ2 (b) Find the MLEs for β and σ2, explicitly showing that they are unique maximizers of the likelihood function Hint: The function g(x)log(x) +1-x...
Please only solve question 1.13. Question 1.12 is only there for reference. Thank you. 1.12 To collect data in an introductory statistics course, recently I gave the students a questionnaire. One question asked whether the student was a vegetarian. Of 25 students, 0 answered "yes." They were not a random sample, but let us use these data to illustrate inference for a proportion. (You may wish to refer to Section l-4-1 on methods of inference.) Let π denote the population...
Question 5-7 2 Gamma waiting times (frequentist) Suppose we model a sample of times between arrivals of the 1 train of the New York City subway at the 116th Street station, y1, . . . , Yn, as IID random variables Y1, ... , Yn sampled from a Gam(v, 1) distribution, for some unknown v and X. 1. What is the joint log-likelihood, In fy ...Y|0,1(91, ... , Yn | v, 4)? [5 mark(s)] 2. For a fixed value of...
Please give detailed steps. Thank you. 2. Consider the following joint distribution of two discrete variables X and Y: fx,y(x, y) 01 2 3 お88 Recall that the marginal distribution of X is defined as: fx(x) and the marginal distribution of Y is defined as fy(v) -xf(i) Find fx(x) and fy(y) in the support of X and Y (or in simpler terms, find 1), P(Y = 0), P(Y-1), P(Y-2) and P(Y P(X-0), P(X 3)) b. The conditional density of Y...