The `stdlib-js/stats-base-dists-t-ctor` project provides a constructor for Student's t-distribution objects in JavaScript, enabling users to create and manipulate t-distributions with customizable degrees of freedom. It is designed for developers and researchers who need to perform statistical analysis, particularly in fields requiring probability distributions and hypothesis testing.
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Test if a value is a number having a positive value.
Student's t distribution cumulative distribution function (CDF).
Student's t distribution entropy.
Student's t distribution excess kurtosis.
Natural logarithm of the cumulative distribution function (CDF) for a Student's t distribution.
Natural logarithm of the probability density function (PDF) for a Student's t distribution.
Student's t distribution expected value.
Student's t distribution median.
Student's t distribution mode.
Student's t distribution probability density function (PDF).
Student's t distribution quantile function.
Student's t distribution skewness.
Student's t distribution standard deviation.
Student's t distribution variance.
Insert supplied variable values into a format string.
Define a non-enumerable read-only accessor.
Define a non-enumerable read-only property.
Define (or modify) an object property.
Format an error message for production.
Test if an object has a specified property.
Test if a value is a function.
Difference between one and the smallest value greater than one that can be represented as a double-precision floating-point number.
Test if a double-precision floating-point numeric value is NaN.
Create an array containing pseudorandom numbers drawn from a continuous uniform distribution.
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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