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Functions442 in github.com/al-jshen/compute

⨍ Functions 442◇ Types & classes 42

Functiontest_var

src/statistics/moments.rs:139

Functiontest_welford_mean

src/statistics/moments.rs:109

Integrate a function `f` from `a` to `b` using the [trapezoid rule](https://en.wikipedia.org/wiki/Trapezoidal_rule) with `n` partitions.

src/integrate/functions.rs:8

Functionttest_1s

Calculates the t-test for the mean of one set of data. It tests for the null hypothesis that the mean of a sample of independent observations `data` i

src/statistics/tests.rs:4

Functionttest_2s_student

Calculates the Student's t-test for two independent samples, assuming equal variance. This is less reliable than Welch's t-test. See <https://en.wikip

src/statistics/tests.rs:10

Functionttest_2s_welch

Calculates Welch's t-test for two independent samples, without assuming equal variance. It tests the hypothesis that the two populations have equal me

src/statistics/tests.rs:18

src/optimize/lbfgs.rs:7

(&mut self, params: &[f64])

src/distributions/normal.rs:83

(&mut self, params: &[f64])

src/distributions/exponential.rs:56

(&mut self, params: &[f64])

src/distributions/chi_squared.rs:46

(&mut self, params: &[f64])

src/distributions/gamma.rs:82

(&mut self, params: &[f64])

src/distributions/bernoulli.rs:56

(&mut self, params: &[f64])

src/distributions/pareto.rs:55

(&mut self, params: &[f64])

src/distributions/t.rs:45

(&mut self, params: &[f64])

src/distributions/beta.rs:69

(&mut self, params: &[f64])

src/distributions/gumbel.rs:59

(&mut self, params: &[f64])

src/distributions/discreteuniform.rs:54

(&mut self, params: &[f64])

src/distributions/poisson.rs:52

(&mut self, params: &[f64])

src/distributions/uniform.rs:55

(&mut self, params: &[f64])

src/distributions/binomial.rs:71

Returns the variance of the given Normal distribution.

src/distributions/normal.rs:111

src/distributions/exponential.rs:88

Calculates the variance of the Chi square distribution.

src/distributions/chi_squared.rs:79

Calculates the variance of the given Gamma distribution.

src/distributions/gamma.rs:114

Calculates the variance, given by `p*q = p(1-p)`.

src/distributions/bernoulli.rs:88

Calculates the variance of the Pareto distribution.

src/distributions/pareto.rs:90

Calculates the variance of the T distribution. # Remarks This is not defined when degrees of freedom is less than or equal to 1, and infinity when de

src/distributions/t.rs:81

Returns the variance of the beta distribution.

src/distributions/beta.rs:100

src/distributions/multivariatenormal.rs:110

Calculates the variance of the given Gumbel distribution.

src/distributions/gumbel.rs:84

Calculates the variance of the given Uniform distribution.

src/distributions/discreteuniform.rs:87

Calculates the variance, which is given by the rate parameter.

src/distributions/poisson.rs:82

Calculates the variance of the given Uniform distribution.

src/distributions/uniform.rs:89

Calculates the variance, which is given by `npq`, where `q = 1-p`

src/distributions/binomial.rs:287

Vertical concatenation of matrices. Adds `other` below the calling matrix.

src/linalg/array/matrix.rs:460

Repeat self vertically. That is, make `n` total copies of self and vertically concatenate them all together.

src/linalg/array/matrix.rs:486

Methodwith_capacity

src/linalg/array/vec.rs:34

Methodwith_capacity

Make an empty matrix with a certain capacity.

src/linalg/array/matrix.rs:45

Methodwith_shape

Make a matrix with a given shape, initialized with garbage values.

src/linalg/array/matrix.rs:54

Methodwith_stepsize

(stepsize: f64)

src/optimize/adam.rs:67

src/linalg/array/vec.rs:58

Make a matrix filled with zeros.

src/linalg/array/matrix.rs:35

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