stdlib-js/assert-is-number

Detect native Symbol.toStringTag support.

Number constructor.

Define a non-enumerable read-only property.

Determine the specification defined classification of an object.

Detect native Symbol support.

Test if a value is a boolean.

Proxies nodejs require in order to allow overriding dependencies during testing.

tap-producing test harness for node and browsers

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Minimal TAP output formatter.

Benchmark harness.

Test if a value is a number having an integer value.

Test if a value is a number having a positive value.

Create an iterator which invokes a unary function accepting a single numeric argument for each iterated value.

Test if a value is a number having a nonnegative value.

128-bit complex number.

Test if a value is NaN.

64-bit complex number.

Test if a value is a probability.

Test if a value is an array-like object of numbers.

Uniformly distributed pseudorandom numbers.

Raised cosine distributed pseudorandom numbers.

Normally distributed pseudorandom numbers.

Compute a moving corrected sample standard deviation incrementally.

Log-normally distributed pseudorandom numbers.

Arcsine distributed pseudorandom numbers.

Laplace (double exponential) distributed pseudorandom numbers.

Cauchy distributed pseudorandom numbers.

Fréchet distributed pseudorandom numbers.

Gumbel distributed pseudorandom numbers.

Create an iterator which invokes a binary function accepting numeric arguments for each iterated value.

Negative binomial distributed pseudorandom numbers.

Lévy distributed pseudorandom numbers.

Triangular distributed pseudorandom numbers.

Logistic distributed pseudorandom numbers.

Compute a corrected sample standard deviation incrementally.

Compute a moving sample Pearson product-moment correlation coefficient incrementally.

Compute a sample Pearson product-moment correlation coefficient.

Compute an unbiased sample variance incrementally.

Test if a value is an infinite number.

Test if a value is a finite number.

Create a readable stream for generating pseudorandom numbers drawn from a uniform distribution.

Create a readable stream for generating pseudorandom numbers drawn from a Fréchet distribution.

Compute a moving unbiased sample variance incrementally.

Perform a one-way analysis of variance.

Create a readable stream for generating pseudorandom numbers drawn from a normal distribution.

Create a readable stream for generating pseudorandom numbers drawn from a triangular distribution.