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The exponential distribution is the special case of a Gamma distribution with shape parameter 1. If X ~ Exp (λ) and Xi ~ Exp (λ i) then: , closure under scaling by a positive factor. 1 + X ~ BenktanderWeibull (λ, 1), which reduces to a truncated exponential distribution. keX ~ Pareto ( k, λ). e−X ~ Beta (λ, 1).
The reciprocal 1/ X of a random variable X, is a member of the same family of distribution as X, in the following cases: Cauchy distribution, F distribution, log logistic distribution . Examples: If X is a Cauchy ( μ, σ) random variable, then 1/ X is a Cauchy ( μ / C, σ / C) random variable where C = μ2 + σ2.
The Weibull distribution or Rosin Rammler distribution, of which the exponential distribution is a special case, is used to model the lifetime of technical devices and is used to describe the particle size distribution of particles generated by grinding, milling and crushing operations. The modified half-normal distribution.
A single-parameter exponential family is a set of probability distributions whose probability density function (or probability mass function, for the case of a discrete distribution) can be expressed in the form. where and are known functions. The function must be non-negative.
The gamma distribution is the maximum entropy probability distribution (both with respect to a uniform base measure and a base measure) for a random variable X for which E[X] = kθ = α/β is fixed and greater than zero, and E[ln X] = ψ(k) + ln θ = ψ(α) − ln β is fixed ( ψ is the digamma function ). [1]
The quantile function, Q, of a probability distribution is the inverse of its cumulative distribution function F. The derivative of the quantile function, namely the quantile density function, is yet another way of prescribing a probability distribution. It is the reciprocal of the pdf composed with the quantile function.
Memorylessness. In probability and statistics, memorylessness is a property of certain probability distributions. It describes situations where the time you've already waited for an event doesn't affect how much longer you'll have to wait. To model memoryless situations accurately, we have to disregard the past state of the system – the ...
has a geometric distribution taking values in the set {0, 1, 2, ...}, with expected value r/(1 − r). [citation needed] The exponential distribution is the continuous analogue of the geometric distribution. If X is an exponentially distributed random variable with parameter λ, then