Question

Please answer the question clearly.

Consider a random sample of size n from a Poisson population with parameter λ (a) Find the method of moments estimator for λ.

0 0
Add a comment Improve this question Transcribed image text
Answer #1

Gven that et gamma ditbibution) ametas d and Conce. dibibution inta 15 17户 Malo ) сх . X on vWe can .tas -bollows: 행on 04 A. and gamma poamehu ale the above ct itel we mu and with dlistibilion -^unction e aarnma we aciut +his the Cortant valit as +uDua twe can om-H勍ʼ upe calculate the mean Torn the above eg/17. 너β cll dt9A广 a AnNote :As per HomeworkLib rules,we answered only one question at a time,if you have any doubts in this answer please comment me.And if you want the answer for question 1 please upload it as another question.

Add a comment
Know the answer?
Add Answer to:
Please answer the question clearly. Consider a random sample of size n from a Poisson population...
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for? Ask your own homework help question. Our experts will answer your question WITHIN MINUTES for Free.
Similar Homework Help Questions
  • 3. Let Xi, , Xn be a random sample from a Poisson distribution with p.m.f Assume...

    3. Let Xi, , Xn be a random sample from a Poisson distribution with p.m.f Assume the prior distribution of Of λ is is an exponential with mean 1, i.e. the prior pdi g(A) e-λ, λ > 0 Note that the exponential distribution is a special gamma distribution; and a general gamma distribution with parameters α > 0 and β > 0 has the pd.f. h(A; α, β)-16(. otherwise Also the mean of a gamma random variable with the pd.f.h(Χα,...

  • Random variable X corresponds to the daily number of accidents in a small town during the...

    Random variable X corresponds to the daily number of accidents in a small town during the first week of January. From the previous experience (prior infor- mation), local police Chief Smith tends to believe that the mean daily number of accidents is 2 and the variance is also 2. We also observe for the current year the sample number of accidents for 5 days in a row: 5,2,1,3,3. Let us assume that X has Poisson distribution with parameter θ ....

  • Problem 3.1 Suppose that XI, X2,... Xn is a random sample of size n is to...

    Problem 3.1 Suppose that XI, X2,... Xn is a random sample of size n is to be taken from a Bermoulli distribution for which the value of the parameter θ is unknown, and the prior distribution of θ is a Beta(α,β) distribution. Represent the mean of this prior distribution as μο=α/(α+p). The posterior distribution of θ is Beta =e+ ΣΧ, β.-β+n-ΣΧ.) a) Show that the mean of the posterior distribution is a weighted average of the form where yn and...

  • (al This question asks you to consider a Bayesian approach to inference about λ, the mortality rate in an exponential model for survival time. In order to take a Bayesian . Show that the gamma distri...

    (al This question asks you to consider a Bayesian approach to inference about λ, the mortality rate in an exponential model for survival time. In order to take a Bayesian . Show that the gamma distribution is a conjugate prior distribution for the distribution is also Gamma, with parameters that depend on a, P, n,y. approach, we specify a prior distribution for A which is gamma distribution exponential model, ie. if we specify that λ~Gamma (α, β) a priori, then...

  • Consider a random sample of size n from an infinite population with mean μ and variance...

    Consider a random sample of size n from an infinite population with mean μ and variance σ2. 6. Consider a random sample of size n from an infinite population with mean μ and variance σ2. (a) Find the method of moments estimator for μ in terms of the sample moments (b) Find the method of moments estimator for σ2 in terms of the sample moments.

  • Let X1, . . . , Xn be a random sample following Gamma(2, β) for some...

    Let X1, . . . , Xn be a random sample following Gamma(2, β) for some unknown parameter β > 0. (i) Now let’s think like a Bayesian. Consider a prior distribution of β ∼ Gamma(a, b) for some a, b > 0. Derive the posterior distribution of β given (X1, . . . , Xn) = (x1,...,xn). (j) What is the posterior Bayes estimator of β assuming squared error loss?

  • Let Xi , i = 1, · · · , n be a random sample from...

    Let Xi , i = 1, · · · , n be a random sample from Poisson(θ) with pdf f(x|θ) = e −θ θ x x! , x = 0, 1, 2, · · · . (a) Find the posterior distribution for θ when the prior is an exponential distribution with mean 1; (b) Find the Bayesian estimator under the square loss function. (c) Find a 95% credible interval for the parameter θ for the sample x1 = 2, x2...

  • . A random sample of size n is taken from a population that has a distri- bution with density fun...

    . A random sample of size n is taken from a population that has a distri- bution with density function given by 0, elsewhere Find the likelihood function L(n v.. V ) -Using the factorization criterion, find a sufficient statistic for θ. Give your functions g(u, 0) and h(i, v2.. . n) - Use the fact that the mean of a random variable with distribution function above is to find the method of moment's estimator for θ. Explain how you...

  • The Pareto probability distribution has many applications in economics, biology, and physics. Let β> 0 and...

    The Pareto probability distribution has many applications in economics, biology, and physics. Let β> 0 and δ> 0 be the population parameters, and let XI, X2, , Xn be a random sample from the distribution with probability density function zero otherwise. Suppose B is known Recall: a method of moments estimator of δ is δ = the maximum likelihood estimator of δ is δ In In X-in β has an Exponential (0--) distribution Suppose S is known Recall Fx(x) =...

  • B1. A random sample of n observations, Yi, ., Yn, is selected from a pop- ulation...

    B1. A random sample of n observations, Yi, ., Yn, is selected from a pop- ulation in which Yi, for i = 1, 2, ,n, possesses a common distribution the same as that of the population distribution Y (a) Suppose that we know Y has a Geometric distribution with parameter p, p unknown. Find the estimator using the method of moments. (b) Suppose that we know that Y has an exponential distribution with parameter λ, λ unknown. Find the estimator...

ADVERTISEMENT
Free Homework Help App
Download From Google Play
Scan Your Homework
to Get Instant Free Answers
Need Online Homework Help?
Ask a Question
Get Answers For Free
Most questions answered within 3 hours.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT