Simulation & Probabilistic Analysis SDK
Add Distribution Fitting & Simulation Features to Your Applications

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Probability Density Function

The probability density function (PDF) is the probability that the variate has the value x:

For discrete distributions, the empirical (sample) PDF is displayed as vertical lines representing the probability mass at each integer x. The theoretical (fitted) PDF is displayed as a polygonal line for better perception, though it is defined for integer x values only:

For continuous distributions, the PDF is expressed in terms of an integral between two points:

In this case, the empirical PDF is displayed as a histogram consisting of equal-width vertical bars (bins), each representing the number of sample data values (falling into the corresponding interval), divided by the total number of data points. The theoretical PDF is displayed as a continuous curve properly scaled depending on the number of intervals. The scaling means multiplying the PDF values by the interval width:

The SDK automatically calculates the number of intervals (bins) depending on the sample size. You can also specify this number manually.

See also:

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