![Exercice 1: Consider a random variable X with the following probabilities distribution: 2 where α1 and α2 are parameters such that 0 < αι < 1,0 < α2 < 1 and αί+a2 1. 1) Compute E[X] and E[X21. 2) Find aǐ and , two estimators of α1 and α2, using the Method of Moments. 3) We assume that: 7t 7 1 1-1 i=1 is as unbiased?](http://img.homeworklib.com/questions/4b93e360-fa40-11eb-9b72-119d04c238c9.png?x-oss-process=image/resize,w_560)
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Exercice 1: Consider a random variable X with the following probabilities distribution: 2 where α1 and...
Exercise 1: Probability Distribution Please give detailed steps for questions 2 & 3, I have seen...
Exercise 1: Probability Distribution
Please give detailed steps for questions 2 & 3, I have seen
the explanation before but it remains unclear.
Exercice 1 Consider a random variable X with the following probabilities distribution: where α1 and α2 are parameters such that 0 < αι < 1,0 < α2 1 and α1taz 1. 1) Compute E[X] and E[X2]. 2) Find a. and az, two estimators of«, and α2, using the Method of Moments. 3)we assume that 22-1-12,xf 7t 6,...
1. Consider a variable y = θ+e where θ is an unknown parameter and e is a random variable with me...
1. Consider a variable y = θ+e where θ is an unknown parameter and e is a random variable with mean zero (a) What is the expected value of y (b) Suppose you draw a sample of in y-Derive the least squares estimator for θ. For full credit you must check the 2nd order condition. (c) Can this estimator () be described as a method of moments estimator? (d) Now suppose e is independent normally distributed with mean 0 and...
2). Consider a discrete random variable X whose cumulative distribution function (CDF) is given by 0...
2). Consider a discrete random variable X whose cumulative distribution function (CDF) is given by 0 if x < 0 0.2 if 0 < x < 1 Ex(x) = {0.5 if 1 < x < 2 0.9 if 2 < x <3 11 if x > 3 a)Give the probability mass function of X, explicitly. b) Compute P(2 < X < 3). c) Compute P(x > 2). d) Compute P(X21|XS 2).
Question 5 15 marks] Let X be a random variable with pdf -{ fx(z) = - 0<r<1 (1) 0 :otherwise, Xa, n>2, be...
Question 5 15 marks] Let X be a random variable with pdf -{ fx(z) = - 0<r<1 (1) 0 :otherwise, Xa, n>2, be iid. random variables with pdf where 0> 0. Let X. X2.... given by (1) (a) Let Ylog X, where X has pdf given by (1). Show that the pdf of Y is Be- otherwise, (b) Show that the log-likelihood given the X, is = n log0+ (0- 1)log X (0 X) Hence show that the maximum likelihood...
I. Consider a variable y = θ + where θ is an unknown parameter and e is a random variable with me...
I. Consider a variable y = θ + where θ is an unknown parameter and e is a random variable with mean zero. (a) What is the expected value of y? (b) Suppose you draw a sample of yi yn. Derive the least squares estimator for θ. For full credit you must check the 2nd order condition c) Can this estimator (0) be described as a method of moments estimator? (d) Now suppose є is independent normally distributed with mean...
a) Consider a random sample {X1, X2, ... Xn} of X from a uniform distribution over...
a) Consider a random sample {X1, X2, ... Xn} of X from a uniform distribution over [0,0], where 0 <0 < co and e is unknown. Is п Х1 п an unbiased estimator for 0? Please justify your answer. b) Consider a random sample {X1,X2, ...Xn] of X from N(u, o2), where u and o2 are unknown. Show that X2 + S2 is an unbiased estimator for 2 a2, where п п Xi and S (X4 - X)2. =- п...
Problem 6. [Poisson is Pronounced 'Pwah-ssohn] (a) Suppose that X is a random variable following the...
Problem 6. [Poisson is Pronounced 'Pwah-ssohn] (a) Suppose that X is a random variable following the Poisson distribution with rate parameter A. Show that E[x]-A Hint: You may find the following fact useful: at k! (b) Suppose that we obtained the following count data: Count Frequency 24 30 17 19 Fit a Poisson distribution to the data using the Method of Moments (c) Suppose that X is a random variable that follows the Poisson distribution that you fit in part...
1. Let X1, ..., Xn be a random sample from a distribution with the pdf le-x/0,...
1. Let X1, ..., Xn be a random sample from a distribution with the pdf le-x/0, x > 0, N = (0,00). (a) Find the maximum likelihood estimator of 0. (b) Find the method of moments estimator of 0. (c) Are the estimators in a) and b) unbiased? (d) What is the variance of the estimators in a) and b)? (e) Suppose the observed sample is 2.26, 0.31, 3.75, 6.92, 9.10, 7.57, 4.79, 1.41, 2.49, 0.59. Find the maximum likelihood...
Having troubles with question 2. Please help 2. If X has a Gamma distribution with parameters...
Having troubles with question 2. Please help
2. If X has a Gamma distribution with parameters a and B, then its mgf is given by (a) Obtain expressions for the moment-genérating functions of an exponential random variable and of a chi-square random variable by recognizing that these are special cases of a Gamma distribution and using the mgf given above. (b) Suppose that X1 is a Gamma variable with parameters α1 and β, X2 is a Gamma variable with parameters...
1. Consider a discrete random variable, X, where the outcome of this random variable is determined...
1. Consider a discrete random variable, X, where the outcome of this random variable is determined by throwing a 6-sided die. X takes on integer values 1,2,…,6. The die is fair. That is, P(X=1)= P(X=2)=…= P(X=6). i. Draw the probability distribution function for this random variable. Carefully label the graph. ii. Draw the cumulative distribution function for X. iii. Calculate the following: P(X=4) P(X≠5) P(X=1 or X=6) P(X4) E(X) Var(X) sd(X) iv. Consider the random variable Y where the outcome...
Exercise 1: Probability Distribution
Please give detailed steps for questions 2 & 3, I have seen
the explanation before but it remains unclear.
Exercice 1 Consider a random variable X with the following probabilities distribution: where α1 and α2 are parameters such that 0 < αι < 1,0 < α2 1 and α1taz 1. 1) Compute E[X] and E[X2]. 2) Find a. and az, two estimators of«, and α2, using the Method of Moments. 3)we assume that 22-1-12,xf 7t 6,...
1. Consider a variable y = θ+e where θ is an unknown parameter and e is a random variable with mean zero (a) What is the expected value of y (b) Suppose you draw a sample of in y-Derive the least squares estimator for θ. For full credit you must check the 2nd order condition. (c) Can this estimator () be described as a method of moments estimator? (d) Now suppose e is independent normally distributed with mean 0 and...
2). Consider a discrete random variable X whose cumulative distribution function (CDF) is given by 0 if x < 0 0.2 if 0 < x < 1 Ex(x) = {0.5 if 1 < x < 2 0.9 if 2 < x <3 11 if x > 3 a)Give the probability mass function of X, explicitly. b) Compute P(2 < X < 3). c) Compute P(x > 2). d) Compute P(X21|XS 2).
Question 5 15 marks] Let X be a random variable with pdf -{ fx(z) = - 0<r<1 (1) 0 :otherwise, Xa, n>2, be iid. random variables with pdf where 0> 0. Let X. X2.... given by (1) (a) Let Ylog X, where X has pdf given by (1). Show that the pdf of Y is Be- otherwise, (b) Show that the log-likelihood given the X, is = n log0+ (0- 1)log X (0 X) Hence show that the maximum likelihood...
I. Consider a variable y = θ + where θ is an unknown parameter and e is a random variable with mean zero. (a) What is the expected value of y? (b) Suppose you draw a sample of yi yn. Derive the least squares estimator for θ. For full credit you must check the 2nd order condition c) Can this estimator (0) be described as a method of moments estimator? (d) Now suppose є is independent normally distributed with mean...
a) Consider a random sample {X1, X2, ... Xn} of X from a uniform distribution over [0,0], where 0 <0 < co and e is unknown. Is п Х1 п an unbiased estimator for 0? Please justify your answer. b) Consider a random sample {X1,X2, ...Xn] of X from N(u, o2), where u and o2 are unknown. Show that X2 + S2 is an unbiased estimator for 2 a2, where п п Xi and S (X4 - X)2. =- п...
Problem 6. [Poisson is Pronounced 'Pwah-ssohn] (a) Suppose that X is a random variable following the Poisson distribution with rate parameter A. Show that E[x]-A Hint: You may find the following fact useful: at k! (b) Suppose that we obtained the following count data: Count Frequency 24 30 17 19 Fit a Poisson distribution to the data using the Method of Moments (c) Suppose that X is a random variable that follows the Poisson distribution that you fit in part...
1. Let X1, ..., Xn be a random sample from a distribution with the pdf le-x/0, x > 0, N = (0,00). (a) Find the maximum likelihood estimator of 0. (b) Find the method of moments estimator of 0. (c) Are the estimators in a) and b) unbiased? (d) What is the variance of the estimators in a) and b)? (e) Suppose the observed sample is 2.26, 0.31, 3.75, 6.92, 9.10, 7.57, 4.79, 1.41, 2.49, 0.59. Find the maximum likelihood...
Having troubles with question 2. Please help
2. If X has a Gamma distribution with parameters a and B, then its mgf is given by (a) Obtain expressions for the moment-genérating functions of an exponential random variable and of a chi-square random variable by recognizing that these are special cases of a Gamma distribution and using the mgf given above. (b) Suppose that X1 is a Gamma variable with parameters α1 and β, X2 is a Gamma variable with parameters...
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