3. We continue the topic of unemployment duration in small towns; we assume that in general it follows a T(k, A) distri...
Assume that we have three independent observations: where Xi ~ Binomial(n 7,p) for i E { 1.2.3). The value of p E (0, 1) is not known. When we have observations like this from different, independent ran- dom variables, we can find joint probabilities by multiplying together th ndividual probabilities. For example This should remind you the discussion on statistical independence of random variables that can be found in the course book (see page 22) Answer the following questions a...
2- 5. The Weibull distribution has many applications in reliability engineering, survival analysis, and general insurance. Let B>0, 8>0. Consider the probability density function x>0 zero otherwise Recall (Homework #1) V-Χδ has an Exponential(8-T )-Gamma(u-l,e-1 ) distribution. Let X1, . , X/ be a random sample from the above probability distribution. y-ΣΧ.Σν i has a Gamma(u-n, θ- 1 ) distribution. !!! i-l 2. suppose δ is known. Let Xi, X2, , Xn be a random sample from the distribution with...
Suppose observations X1, X2,.. are recorded. We assume these to be conditionally independent and exponen- tially distributed given a parameter θ: Xi ~' Exponential(θ), for all i 1, . . . , n. The exponential distribution is controlled by one rate parameter θ > 0, and its density is for r ER+ 1. Plot the graph of p(x:0) for θ 1 in the interval x E [0,4] 2. What is the visual representation of the likelihood of individual data points?...
Suppose that X1, … Xn are sample from the following truncated Poisson distribution. 12:35 AM Fri Nov 29 100% 5 TORO+ 0 0 + Bo 2. Suppose that X ., X, are sampled from the following truncated Poisson distribution: PCX = r exp(-)" ! (r) for x=r +1,7 +2,... for some integer r > where *a(r) = Į PM) = 1 - . expe="JA" Such a sample might arise if we were sampling from a Poisson population but were unable...
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,...
Question 2: Suppose that we wish to fit a regression model for which the true regression line passes through the origin (0,0). The appropriate model is Y = Bx + €. Assume that we have n pairs of data (x1.yı) ... (Xn,yn). a) From first principle, derive the least square estimate of B. (write the loss function then take first derivative W.r.t coefficient etc) b) Assume that e is normally distributed what is the distribution of Y? Explain your answer...
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,...
4. Setup: Suppose you have observations X1,X2,X3,X4,X5 which are i.i.d. draws from a Gaussian distribution with unknown mean μ and unknown variance σ2. Given Facts: You are given the following: 15∑i=15Xi=0.90,15∑i=15X2i=1.31 Bookmark this page Setup: Suppose you have observations X1, X2, X3, X4, X5 which are i.i.d. draws from a Gaussian distribution with unknown mean u and unknown variance o? Given Facts: You are given the following: x=030, =1:1 Choose a test 1 point possible (graded, results hidden) To test...