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⨍ Functions 442◇ Types & classes 42

Functionpoisson

(c: &mut Criterion)

benches/benchmark_distributions.rs:31

Returns `c0 + c[1] * x + c[2] * x^2 ... + cn + x^n`, where `c[i]` are the coefficients of the polynomial regressor, and `x` is some vector of explanat

src/predict/polynomial.rs:29

Calculates the product of a vector.

src/linalg/utils.rs:563

Integrate a function `f` from `a` to `b` using the [Gauss-Legendre quadrature method](https://en.wikipedia.org/wiki/Gaussian_quadrature) with 5 points

src/integrate/functions.rs:79

Reshape the matrix. A size of `-1` in either the rows or the columns means that the size for that dimension will be automatically determined if possib

src/linalg/array/matrix.rs:317

Functionromberg

Integrate a function `f` from `a` to `b` using the [Romberg method](https://en.wikipedia.org/wiki/Romberg%27s_method), stopping after either sequentia

src/integrate/functions.rs:18

Functionrosenbrock

(p: &[Var<'a>], d: &[&[f64]])

src/optimize/adam.rs:199

Functionrotation_matrix_ccw

Returns a 3D counter-clockwise rotation matrix along the `axis` axis (either X, Y, or Z) with a given angle in radians. # Remarks These are counter-c

src/linalg/rotations.rs:61

Functionrotation_matrix_cw

Returns a 3D clockwise rotation matrix along the `axis` axis (either X, Y, or Z) with a given angle in radians. # Remarks These are clockwise rotatio

src/linalg/rotations.rs:16

Sample from the given Normal distribution.

src/distributions/normal.rs:52

Samples from the given Exponential distribution. # Remarks Uses the [inverse transform sampling](https://en.wikipedia.org/wiki/Inverse_transform_samp

src/distributions/exponential.rs:50

Samples from the given Chi square distribution.

src/distributions/chi_squared.rs:40

Samples from the given Gamma distribution. # Remarks Uses the algorithm from Marsaglia and Tsang 2000. Applies the squeeze method and has nearly cons

src/distributions/gamma.rs:60

Samples from the given Bernoulli distribution.

src/distributions/bernoulli.rs:40

Samples from the given Pareto distribution using inverse transform sampling.

src/distributions/pareto.rs:48

Samples from the given Beta distribution using the Gamma distribution.

src/distributions/beta.rs:62

src/distributions/multivariatenormal.rs:54

Samples from the given Gumbel distribution.

src/distributions/gumbel.rs:53

Samples from the given discrete uniform distribution.

src/distributions/discreteuniform.rs:48

Samples from the given Poisson distribution. For `lambda < 10.0`, this is done with the direct (multiplication) method, and for `lambda >= 10.0`, this

src/distributions/poisson.rs:42

Samples from the given Uniform distribution.

src/distributions/uniform.rs:49

Functionsample_covariance

Calculates the sample covariance between two vectors x and y. This is a two-pass algorithm which centers the data before computing the covariance, whi

src/statistics/covariance.rs:22

Functionsample_covariance_onepass

Calculates the covariance between two vectors x and y. This is a one-pass algorithm which shifts the data by the first element in each vector before c

src/statistics/covariance.rs:38

Functionsample_covariance_online

Calculates the covariance between two vectors x and y. This is a stable one-pass online algorithm. See <https://en.wikipedia.org/wiki/Algorithms_for_c

src/statistics/covariance.rs:50

Generate a matrix of samples, where each row in the matrix is a random sample from the given distribution.

src/distributions/mod.rs:49

Functionsample_std

Calculates the sample standard deviation of an array of data points. This is the square root of the sample variance.

src/statistics/moments.rs:69

Make some new predictions and calculate the score of those predictions based on known responses.

src/predict/glms/glm.rs:314

Set the model coefficients.

src/predict/glms/glm.rs:57

Methodset_offset

Set the offsets (usually used in Poisson regression models).

src/predict/glms/glm.rs:69

Methodset_penalty

Set the L2 (ridge regression) regularization strength.

src/predict/glms/glm.rs:45

Methodset_stepsize

(&mut self, stepsize: f64)

src/optimize/sgd.rs:59

Methodset_tolerance

Set the convergence tolerance.

src/predict/glms/glm.rs:51

Methodset_weights

Set the sample weights (usually measurement errors).

src/predict/glms/glm.rs:63

Functionshuffle

Shuffle an array.

src/validation/resample.rs:37

Functionshuffle_two

Shuffle two arrays. The same shuffling is applied to both arrays. That is, a pair (x_i, y_i) will still be paired together as (x_j, y_j) after shuffli

src/validation/resample.rs:49

src/linalg/array/vec.rs:48

src/linalg/array/vec.rs:52

(c: &mut Criterion)

benches/benchmark_distributions.rs:49

Functiontest_acf_acovf

src/timeseries/functions.rs:45

Functiontest_adam_rosenbrock

src/optimize/adam.rs:194

Functiontest_adam_slr

src/optimize/adam.rs:152

Functiontest_ar_model

src/timeseries/autoregressive.rs:91

Functiontest_argmax

src/statistics/order.rs:134

Functiontest_argmin

src/statistics/order.rs:72

Functiontest_bernoulli

src/distributions/bernoulli.rs:100

Functiontest_beta

src/functions/gamma.rs:82

Functiontest_binom_methods

src/functions/combinatorial.rs:38

Functiontest_binom_pascal

src/functions/combinatorial.rs:54

Functiontest_bootstrap_moments

src/validation/resample.rs:79

Functiontest_bootstrap_range

src/validation/resample.rs:69

Functiontest_broadcast_1

src/linalg/array/broadcast.rs:184

Functiontest_broadcast_2

src/linalg/array/broadcast.rs:241

Functiontest_broadcast_3

src/linalg/array/broadcast.rs:330

Functiontest_broadcast_4

src/linalg/array/broadcast.rs:342

Functiontest_cdf

src/distributions/normal.rs:427

Functiontest_cholesky

src/linalg/decomposition/cholesky.rs:49

Functiontest_cholesky

src/linalg/array/matrix.rs:985

Functiontest_cholesky_solve

src/linalg/decomposition/cholesky.rs:92

Functiontest_covariance

src/statistics/covariance.rs:75

Functiontest_digamma

src/functions/gamma.rs:92

Functiontest_erf

src/functions/statistical.rs:129

Functiontest_fits

src/predict/polynomial.rs:79

Functiontest_gamma

src/functions/gamma.rs:73

Functiontest_glm_logistic

src/predict/glms/glm.rs:327

Functiontest_hist_bin_centers

src/statistics/hist.rs:24

Functiontest_integrators

src/integrate/functions.rs:116

Functiontest_interp1d_linear_1

src/functions/interpolate.rs:128

Functiontest_interp1d_linear_2

src/functions/interpolate.rs:146

Functiontest_invert

src/linalg/utils.rs:634

Functiontest_jackknife_mean

src/validation/resample.rs:101

Functiontest_jackknife_size

src/validation/resample.rs:92

Functiontest_lbfgs

src/optimize/lbfgs.rs:18

Functiontest_linspace

src/linalg/utils.rs:747

Functiontest_logistic

src/functions/statistical.rs:78

Functiontest_logit

src/functions/statistical.rs:96

Functiontest_lu

src/linalg/decomposition/lu.rs:88

Functiontest_mat_vec_ops

src/linalg/array/matrix.rs:916

Functiontest_matmul

src/linalg/utils.rs:680

Functiontest_matrix_argminmax

src/linalg/array/matrix.rs:1030

Functiontest_max

src/statistics/order.rs:103

Functiontest_mean

src/statistics/moments.rs:79

Functiontest_min

src/statistics/order.rs:41

Functiontest_moments

src/distributions/normal.rs:416

Functiontest_moments

src/distributions/exponential.rs:101

Functiontest_moments

src/distributions/chi_squared.rs:92

Functiontest_moments

src/distributions/gamma.rs:126

Functiontest_moments

src/distributions/pareto.rs:106

Functiontest_moments

src/distributions/t.rs:100

Functiontest_moments

src/distributions/beta.rs:113

Functiontest_moments

src/distributions/poisson.rs:133

Functiontest_moments

src/distributions/binomial.rs:299

Functiontest_mvn_pdf

src/distributions/multivariatenormal.rs:122

Functiontest_sample_var

src/statistics/moments.rs:169

Functiontest_sgd_slr

src/optimize/sgd.rs:149

Functiontest_slr

src/predict/polynomial.rs:68

Functiontest_softmax

src/functions/statistical.rs:116

Functiontest_solve

src/linalg/utils.rs:717

Functiontest_std

src/statistics/moments.rs:199

Functiontest_symmetric

src/linalg/utils.rs:823

Functiontest_trapezoid

src/integrate/samples.rs:27

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