Create a R code Use the Metropolis-Hastings algorithm to generate a MCMC sample from the univariate distribution with PDF function:10)2,-) +2. exp(-1(x -(x - 25)2p(x)• Jexp(-7,T E (-00, 00).12.6WE201020304050Use g(a|u) ~ N(µ, o) with calibration parameter o > 0, as proposal distribution.Verify your sample, via histograms, traceplots/meanplots and autocorrelation charts. Record your solution MCMC sample asmy_sample_MCMC.Include a set.seed(xxxx) line, before coding the algorithm. Your answer should include a histogram of the solution MCMC sample, with thetarget density superimposed. The parameter o should be calibrated, to insure good mixing, as well as acceptable autocorrelation. Include theassociated traceplots/meanplots and autocorrelation charts.

The following R code gives a short MCMC routine to sample from the posterior distribution of pp. Try…

Answered: Use the Metropolis-Hastings algorithm…

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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Use the Metropolis-Hastings algorithm to generate a MCMC sample from the univariate distribution with PDF function: p(x) 1 • exp(- (x - 10)2. -+2. exp(- (т — 25)2 , TE (-00, 00). 12.6 7 20 10