Concepts inGenerating gamma variates by a modified rejection technique

Random variate

A random variate is a particular outcome of a random variable: the random variates which are other outcomes of the same random variable would have different values. Random variates are used when simulating processes driven by random influences.  more from Wikipedia

Gamma distribution

In probability theory and statistics, the gamma distribution is a two-parameter family of continuous probability distributions. There are two different parameterizations in common use: With a shape parameter k and a scale parameter ¿. With a shape parameter ¿ = k and an inverse scale parameter ¿ = ¿¿, called a rate parameter. The parameterization with k and ¿ appears to be more common in econometrics and certain other applied fields, where e.g.  more from Wikipedia

Transplant rejection

Transplant rejection occurs when transplanted tissue is rejected by the recipient's immune system, which destroys the transplanted tissue. Transplant rejection can be lessened by determining the molecular similitude between donor and recipient and by use of immunosuppressant drugs after transplant.  more from Wikipedia

Exponential distribution

Exponential Parameters ¿ > 0 rate, or inverse scale Support x ¿ [0, ¿] PDF ¿¿e CDF 1 ¿ e Mean ¿ Median ¿¿ln¿2 Mode 0 Variance ¿ Skewness 2 Ex. kurtosis 6 Entropy 1 ¿ ln(¿) In probability theory and statistics, the exponential distribution (a.k.a. negative exponential distribution) is a family of continuous probability distributions. It describes the time between events in a Poisson process, i.e. a process in which events occur continuously and independently at a constant average rate.  more from Wikipedia

Random variable

In probability and statistics, a random variable or stochastic variable is a variable whose value is subject to variations due to chance (i.e. randomness, in a mathematical sense). As opposed to other mathematical variables, a random variable conceptually does not have a single, fixed value (even if unknown); rather, it can take on a set of possible different values, each with an associated probability.  more from Wikipedia

Data transformation (statistics)

In statistics, data transformation refers to the application of a deterministic mathematical function to each point in a data set ¿ that is, each data point zi is replaced with the transformed value yi = f(zi), where f is a function. Transforms are usually applied so that the data appear to more closely meet the assumptions of a statistical inference procedure that is to be applied, or to improve the interpretability or appearance of graphs.  more from Wikipedia

Normal distribution

In probability theory, the normal (or Gaussian) distribution is a continuous probability distribution that has a bell-shaped probability density function, known as the Gaussian function or informally the bell curve: The parameter ¿ is the mean or expectation (location of the peak) and ¿ is the variance. ¿ is known as the standard deviation. The distribution with ¿ = 0 and ¿ = 1 is called the standard normal distribution or the unit normal distribution.  more from Wikipedia