The data in GD available in the PASWR package are the times until failure in hours for a particular electronic component subjected to an accelerated stress test.
(a) Find the method of moments estimates of α and λ if the data come from a 
distribution.
(b) Create a density histogram of times until failure. Superimpose a gamma distribution using the estimates from part (a) over the density histogram.
(c) Find the maximum likelihood estimates of α and λ if the data come from a 
 distribution by using the function fitdistr () from the MASS package.
(d) Create a density histogram of times until failure. Superimpose a gamma distribution using the estimates from part (c) over the density histogram.
(e) Plot the cumulative distribution for time until failure using the ecdf () function. Superimpose the theoretical cumulative gamma distribution using both the method of moments and the maximum likelihood estimates of α and λ. Which estimates appear to model the data better?
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