What does PDF stand for?

Probability Distribution Function

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Information technology (IT) and computers

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Samples in periodicals archive:

The probability density function of a two-parameter exponential distribution is given by: f(t;[mu],[theta]) = [1/[theta]]exp{-(t-[mu])/[theta]}, t[greater than or equal to][mu] and t[greater than or equal to]0 Where: [mu] = The location parameter [theta]>0 = The scale parameter The probability distribution function is: F(t;[mu],[theta]) = 1-exp{-(t-[mu])/[theta]}.

Inventory management systems with hazardous items of two-parameter ...

1) [FIGURE 1 OMITTED] For millions of fibers, it is impractical to specify the orientation of each fiber and an alternative is to use the probability distribution function [psi]([theta],[empty set]) [1], which describes the probability of finding fibers with orientation ([theta],[empty set]) in the specimen (23).

A simplified method to determine the 3D orientation of an injection ...

6a, the mode of the probability distribution function was observed for chords between 0.

Turbulence characteristics in skimming flows on stepped spillways

The basis for the simulation is generating random numbers and assigning ranges of numbers to values that fit a probability distribution function (otherwise known as Monte Carlo simulation).

Optimizing logistics through operations research

N](x) is the cumulative probability distribution function (CPDF) of the number of fatalities per year, signifying the probability of less than fatalities per year.

Modeling of risk acceptance criteria for tunnel and underground ...

It also replaces uncertain values in existing spreadsheets with probability distribution functions that represent a range to possible values, speeding up the simulations by using multiple processors simultaneously on the same job.

Palisade Euorpe releases new version of risk analysis product

1) where [pi] is profit, Q is output, p, r, and w are the uncertain product price, cost of capital, and wage rate, respectively, representing stochastic random variables with the joint probability distribution function m(p,r,w) defined for p,r,w [greater than] 0 with finite moments.

ON TOTAL PRICE UNCERTAINTY AND THE BEHAVIOR OF A COMPETITIVE FIRM

A very large population is assumed so p(a) can be approximated as a continuous probability density with probability distribution function P(a) = [integral of] p(z)dz between limits a and -[infinity].

Income tax compliance and evasion: a graphical approach