This JavaScript package provides functions for working with Student's t distribution, including calculating the probability density function, cumulative distribution function, and statistical properties like mean and variance. It's designed for developers who need to perform statistical analysis or implement t-tests in their JavaScript applications, particularly those working in scientific computing or data analysis contexts.
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Support the dependencies of stdlib-js/stats-base-dists-t
Student's t distribution cumulative distribution function (CDF).
Student's t distribution constructor.
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.
Define a read-only property.
Test if an object has a specified property.
Test if a value is a function.
Test if a value is a number having a positive value.
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.
Natural logarithm of 1/2.
Double-precision floating-point negative infinity.
Double-precision floating-point positive infinity.
Test if a double-precision floating-point numeric value is NaN.
Compute the absolute value of a double-precision floating-point number.
Beta function.
Incomplete beta function.
Natural logarithm of the beta function.
Digamma function.
Inverse incomplete beta function.
Evaluate the natural logarithm of a double-precision floating-point number.
Evaluate the natural logarithm of 1+x.
Exponential function.
Evaluate the signum function for a double-precision floating-point number.
Compute the principal square root of a double-precision floating-point number.
Create an array containing pseudorandom numbers drawn from a discrete uniform distribution.
Create an array containing pseudorandom numbers drawn from a continuous uniform distribution.
Insert supplied variable values into a format string.
Constant function.
Define a non-enumerable read-only accessor.
Define a non-enumerable read-only property.
Define (or modify) an object property.
Return an array of an object's own enumerable property names.
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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