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In mathematics, a generating function is a representation of an infinite sequence of numbers as the coefficients of a formal power series.Generating functions are often expressed in closed form (rather than as a series), by some expression involving operations on the formal series.
In probability theory and statistics, the moment-generating function of a real-valued random variable is an alternative specification of its probability distribution.Thus, it provides the basis of an alternative route to analytical results compared with working directly with probability density functions or cumulative distribution functions.
we can use a variant of the positive-order derivative-based OGF transformations defined in the next sections involving the Stirling numbers of the second kind to obtain an integral formula for the generating function of the sequence, {(,) /!}, and then perform a sum over the derivatives of the formal OGF, () to obtain the result in the previous ...
Assume is discrete random variable taking values on the non-negative integers, which is independent of the , and consider the probability generating function . If the X i {\displaystyle X_{i}} are not only independent but also identically distributed with common probability generating function G X = G X i {\displaystyle G_{X}=G_{X_{i}}} , then
If v s is the starting value of the random walk, the expected value after n steps will be v s + nμ. For the special case where μ is equal to zero, after n steps, the translation distance's probability distribution is given by N (0, n σ 2 ), where N () is the notation for the normal distribution, n is the number of steps, and σ is from the ...
The generator is used in evolution equations such as the Kolmogorov backward equation, which describes the evolution of statistics of the process; its L 2 Hermitian adjoint is used in evolution equations such as the Fokker–Planck equation, also known as Kolmogorov forward equation, which describes the evolution of the probability density ...
In statistics, the method of moments is a method of estimation of population parameters.The same principle is used to derive higher moments like skewness and kurtosis. It starts by expressing the population moments (i.e., the expected values of powers of the random variable under consideration) as functions of the parameters of interest.
In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate; the distance parameter could be any meaningful mono-dimensional measure of the process, such as time ...