This package provides a function to evaluate the cumulative distribution function (CDF) for a Pareto Type I distribution, which is used to calculate the probability that a random variable is less than or equal to a given value. It's designed for developers working on statistical analysis or probability calculations in JavaScript, particularly those who need to model phenomena that follow a Pareto distribution, such as income distributions or city population sizes.
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Support the dependencies of stdlib-js/stats-base-dists-pareto-type1-cdf
Test if a double-precision floating-point numeric value is NaN.
C APIs for registering a Node-API module exporting an interface for invoking a ternary numerical function.
Exponential function.
Constant function.
Define a non-enumerable read-only property.
Load a manifest for compiling source files.
Insert array element values and the result of a callback function into a format string and print the result.
Difference between one and the smallest value greater than one that can be represented as a double-precision floating-point number.
Double-precision floating-point negative infinity.
Double-precision floating-point positive infinity.
Compute the absolute value of a double-precision floating-point number.
Create an array containing pseudorandom numbers drawn from a continuous uniform distribution.
Wrap `require` in a try/catch block.
tap-producing test harness for node and browsers
Yet another JS code coverage tool that computes statement, line, function and branch coverage with module loader hooks to transparently add coverage when running tests. Supports all JS coverage use ca
Minimal TAP output formatter.
Benchmark harness.
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