I want to compute the cumulative distribution function in R for data that follows a gamma distribution. I understood how to do this with a lognormal distribution using the equation from Wikipedia; however, the gamma equation seems more complicated and I decided to use the pgamma() function.
I'm new to this and don't understand the following:
- Why do I get three different values out of pgamma, and how does it make sense that they are negative?
- Am I supposed to take the log of all the quantiles, just as I used log(mean) and log(standard deviation) when doing calculations with a lognorm distribution?
- How do I conceptually understand the CDF calculated by pgamma? It made sense for lognorm that I was calculating the probability that X would take a value <= x, but there is no "x" in this pgamma function.
Really appreciate the help in understanding this.
shape <- 1.35721347
scale <- 1/0.01395087
quantiles <- c(3.376354, 3.929347, 4.462594)
pgamma(quantiles, shape = shape, scale = scale, log.p = TRUE)
