Search results
Results from the WOW.Com Content Network
The gamma distribution is a two-parameter exponential family with natural parameters α − 1 and −1/θ (equivalently, α − 1 and −λ), and natural statistics X and ln X. If the shape parameter α is held fixed, the resulting one-parameter family of distributions is a natural exponential family.
Such a parameter must affect the shape of a distribution rather than simply shifting it (as a location parameter does) or stretching/shrinking it (as a scale parameter does). For example, "peakedness" refers to how round the main peak is.
The Gamma distribution, which describes the time until n consecutive rare random events occur in a process with no memory. The Erlang distribution, which is a special case of the gamma distribution with integral shape parameter, developed to predict waiting times in queuing systems; The inverse-gamma distribution; The generalized gamma distribution
A beta-binomial distribution with parameter n and shape parameters α = β = 1 is a discrete uniform distribution over the integers 0 to n. A Student's t-distribution with one degree of freedom (v = 1) is a Cauchy distribution with location parameter x = 0 and scale parameter γ = 1. A Burr distribution with parameters c = 1 and k (and scale λ ...
The inverse gamma distribution's probability density function is defined over the support > (;,) = (/) + (/)with shape parameter and scale parameter. [2] Here () denotes the gamma function.
It is a generalization of the gamma distribution which has one shape parameter (and a scale parameter). Since many distributions commonly used for parametric models in survival analysis (such as the exponential distribution , the Weibull distribution and the gamma distribution ) are special cases of the generalized gamma, it is sometimes used ...
A Weibull distribution is a generalized gamma distribution with both shape parameters equal to k. The translated Weibull distribution (or 3-parameter Weibull) contains an additional parameter. [ 12 ] It has the probability density function
This is the characteristic function of the gamma distribution scale parameter θ and shape parameter k 1 + k 2, and we therefore conclude + (+,) The result can be expanded to n independent gamma distributed random variables with the same scale parameter and we get