Let X be a random variable with p.d.f. f(x) = θx^(θ−1) , for 0 < x < 1. Let X1, ..., Xn denote a random sample of size n from this distribution. (a) Find E(X) [2] (b) Find the method of moment estimator of θ [2] (c) Find the maximum likelihood estimator of θ [3] (d) Use the following set of observations to obtain estimates of the method of moment and maximum likelihood estimators of θ. [1 each] 0.0256, 0.3051, 0.0278, 0.8971, 0.0739, 0.3191, 0.7379, 0.3671, 0.9763, 0.0102
Let X be a random variable with p.d.f. f(x) = θx^(θ−1) , for 0 < x...
Let X be the proportion of impurities in chemical product. The distribution of has the following p.d.f. f(x) = (0+2x+3) x + (1-x) (a) Show that E(X)= *#2 [2] (b) Let X1, ..., X, denote impurities in a random sample of size n of shipment of chemical. Find the method of moment estimator of e. [1] (c) Find the maximum likelihood estimator of 0. [2] (d) Use the following set of 10 proportions of impurities to obtain estimates of the...
1. Let Xi,..., Xn be a random sample from a distribution with p.d.f. f(x:0)-829-1 , 0 < x < 1. where θ > 0. (a) Find a sufficient statistic Y for θ. (b) Show that the maximum likelihood estimator θ is a function of Y. (c) Determine the Rao-Cramér lower bound for the variance of unbiased estimators 12) Of θ
4. Let X1, . . . , Xn be a random sample from a normal random variable X with probability density function f(x; θ) = (1/2θ 3 )x 2 e −x/θ , 0 < x < ∞, 0 < θ < ∞. (a) Find the likelihood function, L(θ), and the log-likelihood function, `(θ). (b) Find the maximum likelihood estimator of θ, ˆθ. (c) Is ˆθ unbiased? (d) What is the distribution of X? Find the moment estimator of θ, ˜θ.
Let X1,..., Xn be a random sample from the pdf f(x:0)-82-2, 0 < θ x < oo. (a) Find the method of moments estimator of θ. (b) Find the maxinum likelihood estimator of θ
Multi-part question: Let X1, .... ,Xn be random variables that describe the accumulated rainfall per month. A) Write the statistical model (there might be more than one suitable statistical model.) B) Assume that the random variables that describe the accumulated rainfall per month have the following p.d.f. Find the moment estimators of a and θ (you can use the results from the table of distributions). C) Under the assumptions in (B) and assuming that a is known, find the maximum...
Let X be a random variable with probability density function (pdf) given by fx(r0)o elsewhere where θ 0 is an unknown parameter. (a) Find the cumulative distribution function (cdf) for the random variable Y = θ and identify the distribution. Let X1,X2, . . . , Xn be a random sample of size n 〉 2 from fx (x10). (b) Find the maximum likelihood estimator, Ỗmle, for θ (c.) Find the Uniform Minimum Variance Unbiased Estimator (UMVUE), Bumvue, for 0...
Multi-part question: Let X1, ..... , Xn be random variables that describe the height of students from a class, in the logarithmic scale. A) Write the statistical model (there might be more than one suitable distribution). B) Assume that X1, ... ,Xn form a random sample from the normal distribution with known mean θ and unknown variance σ^2 . Find the maximum likelihood estimator of the variability of the height (in log scale) of the students, this is, find the...
Will thumbs up if done neatly and correctly! 6-7. Let θ > 1 and let X1,X2, ,Xn be a random sample from the distri- bution with probability density function f(x; θ-zind, 1 < x < θ. 6. a) Obtain the maximum likelihood estimator of θ, θ b) Is a consistent estimator of θ? Justify your answer 6-7. Let θ > 1 and let X1,X2, ,Xn be a random sample from the distri- bution with probability density function f(x; θ-zind, 1
2. Let Xi,... ,Xn be a random sample from a distribution with p.d.f for 0 < x < θ f(x; 0) - 0 elsewhere . (a) Find an estimator for θ using the method of moments. (b) Find the variance of your estimator in (a).
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.