Likelihood留学生讲解、HTML file辅导、讲解Java，c/c++编程、Python语言辅导

Lab Assignment 2

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Likelihood methods for the Poisson distribution

DO NOT CHANGE the chunk name or the set.seed() values below.

Execute each chunk of code to ensure that your code works properly.

Then HTML knit the entire document.

If you cannot compile all of your code without errors before the end of the class, comment out the

chunks that are not working.

Open the HTML document in a browser.

Save the HTML file as a pdf file.

Submit your pdf assignment.

1. First generate 25 observations from the Poisson(lambda=10) distribution and

save them in a vector.

2. Write a function to compute the Log-likelihood for a vector of values of the

mean lambda given the n observations you generated in question 1. Plot the

log-likelihood for a sequence of values of lambda. Axes must be labelled and the

plot must have a title. Ensure that you choose a sequence of lambda values that

bracket the MLE for lambda.

3. Compute the MLE of lambda using the data from question 1 and the function

you defined in question 2 and the optimize() function.

4. Write a function to compute the log relative likelihood - ln(p), r(lambda) -

ln(p) and graph it for a sequence of lambda values and p=.147.

5. Compute the 14.7% Likelihood Interval as the roots of r(lambda) - ln(.147)

= 0. Show the results.