Using log-likelihood method we find out the Maximum likelihood estimators (MLE's):
If we took second derivative to equation 1 with respective to , we get this derivative is less than zero. Hence is the MLE of parameter .
Thus and are the MLE's of for and .
2. Consider the density given by gy (y; a, B) -exp the MLEs for α and...
Consider data that follow an exponential regression with no intercept y ind exp(Bri), where the scalar parameter β 〉 0 is unknown and the x's 〉 0 are fixed and known for , .. . ,n. That is, Yı,... , Yn are independent random variables with density functions for y > 0. Note that E(Y)- Bxi a) Derive the least squares estimator B, i.e., minimize What are the mean and variance of this estimator? (b) Derive the maximum likelihood estimator...
Recall that if X has a beta(a, B) distribution, then the probability density function (pdf) of X is where α > 0 and β > 0. In this problem, we are going to consider the beta subfamily where α-β θ. Let X1, X2, , Xn denote an iid sample from a beta(8,9) distribution. (b) The two-dimensional statistic nm 27 is also a sufficient statistic for θ. What must be true about the conditional distribution (c) Show that T* (X) is...
Let X1, , Xn be a sample of size n from a distribution with the density 0 otherwise where α > 0 and β 0 (so called Weibull distribution). Assuming β is known, find a maximum likelihood estimate for α.
3. Let X be a ry, with m.gj. M given by M()-eat+βι2, ț e R(α e R, β > 0). Find the ch.f. of X and identify its p.d.f. Also, use the ch.f. of X in order to calculate E(X4). at+ Br
Problem 9: 10 points Suppose that X, Y are two independent identically distributed random variables with the density function f(x)= λ exp (-Az), for >0. Consider T- and find its cumulative distribution function and density function.
b. Suppose ~ Γ(α, β), with α > 0, β > 0 and let Y-eu. Find the probability density function of Y Find EY and var(Y)
2. Suppose an exact linear relationship exists between two random variables X and Y That is, let Y-α + ßx, where α and β are constants and β > 0. Prove that ρχ,-1 Hint: Substitute α + βΧ into the formula for Pry and apply the covariance rules.
3. Suppose X ~ Beta(a, β) with the constants α, β > 0, Define Y- 1-X. Find the pdf of Y
Q1. Assume that X is Pareto random variables with the density -α-1 , r21, where α > 0 (a) Calculate EX]. What do you need to assume about a for E[X to be finite? (b) Find the density of X + b for b 〉 0. (c) Find the cumulative distribution function of Y log X.
Suppose a joint probability density function for two variables X and Y is given as follows: {24x0, if 0 < x < 1,0 < y < 1 f(x, y) = otherwise Please find the probability p (w > 1) =? 3