R Statistics Cookbook

How to do it...

In this exercise, we will generate a 1000 random gamma deviates with its two parameters set to shape=20 and rate=2. We will then estimate the two parameters by using the mle2 function in the bbmle package. This function will also return the Z values, and the p-values. Note that we need to assume a distribution that we will use to fit the parameters (in general we will receive data, and we will need to assume which distribution is reasonable). In this case, since we are generating the data, we already know that the data comes from a gamma distribution.

We will use the bbmle package, which will allow us to maximize the log-likelihood. This package essentially wraps an appropriate numerical maximization routine; we only need ...