7. (15 pts) Suppose X1, X2, ..., X, is a random sample from an exponential distribution...
7. Suppose X1, X2, ..., Xn is a random sample from an exponential distribution with parameter K. (Remember f(x;2) = 2e-Ax is the pdf for the exponential dist”.) a) Find the likelihood function, L(X1, X2, ..., Xn). b) Find the log-likelihood function, b = log L. c) Find dl/d, set the result = 0 and solve for 2.
1. Suppose that X1, X2,..., X, is a random sample from an Exponential distribution with the following pdf f(x) = 6, x>0. Let X (1) = min{X1, X2, ... , Xn}. Consider the following two estimators for 0: 0 =nX) and 6, =Ỹ. (a) Show that ő, is an unbiased estimator of 0. (b) Find the relative efficiency of ô, to ô2.
Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = (1/θ)e^(−x/θ) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ. Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = θe^(−θx) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ.
4. Let X1, X2, ..., Xn be a random sample from an Exponential(1) distribution. (a) Find the pdf of the kth order statistic, Y = X(k). (b) Determine the distribution of U = e-Y.
Advanced Statistics, I need help with (c) and (d) 2. Let X1, X2, ..., Xn be a random sample from a Bernoulli(6) distribution with prob- ability function Note that, for a random variable X with a Bernoulli(8) distribution, E [X] var [X] = θ(1-0) θ and (a) Obtain the log-likelihood function, L(0), and hence show that the maximum likelihood estimator of θ is 7l i= I (b) Show that dE (0) (c) Calculate the expected information T(e) EI()] (d) Show...
4 10 pts. Let X1 X2 be a random sample from the exponential distribution with parameter θ What is the mgf of Y = X1 + X2? a) (4 pts.+) Find E(Y-E(X1 + X2] using the mgf. For 2 more points on test 2: How is Y distributed? 4 10 pts. Let X1 X2 be a random sample from the exponential distribution with parameter θ What is the mgf of Y = X1 + X2? a) (4 pts.+) Find E(Y-E(X1...
2. (a) Suppose that x1,... , Vn are a random sample from a gamma distribution with shape parameter α and rate parameter λ, Here α > 0 and λ > 0. Let θ-(α, β). Determine the log-likelihood, 00), and a 2-dimensional sufficient statistic for the data (b) Suppose that xi, ,Xn are a random sample from a U(-9,0) distribution. f(x; 8) otherwise Here θ > 0, Determine the likelihood, L(0), and a one-dimensional sufficient statistic. Note that the likelihood should...
Let X1, X2, . . . , Xn be a random sample from some distribution and suppose Y = T(X1, X2, . . . , Xn) is a statistic. Suppose the sampling distribution of Y has PDF fY (y) = 3 8 y 2 for 0 ≤ y ≤ 2. Find P[0 ≤ Y ≤ 1 5 ].
Let X1,X2,...,Xn denote a random sample from the Rayleigh distribution given by f(x) = (2x θ)e−x2 θ x > 0; 0, elsewhere with unknown parameter θ > 0. (A) Find the maximum likelihood estimator ˆ θ of θ. (B) If we observer the values x1 = 0.5, x2 = 1.3, and x3 = 1.7, find the maximum likelihood estimate of θ.
I. Let X be a random sample from an exponential distribution with unknown rate parameter θ and p.d.f (a) Find the probability of X> 2. (b) Find the moment generating function of X, its mean and variance. (c) Show that if X1 and X2 are two independent random variables with exponential distribution with rate parameter θ, then Y = X1 + 2 is a random variable with a gamma distribution and determine its parameters (you can use the moment generating...