Re-exports
pub use matrix::*;pub use vector::*;pub use stat::*;pub use r_macro::*;pub use matlab_macro::*;pub use rand::*;Modules
Macros
R like concatenate (Type: Vec<f64>)
R like cbind
MATLAB like eye - identity matrix
MATLAB like linspace
R like lm
More R like Matrix constructor (Macro)
MATLAB like rand - random matrix
R like rbind
R like random uniform
R like seq macro
MATLAB like zeros - zero matrix
Functions
Computes the beta function
where
a is the first beta parameter
and b is the second beta parameter.Computes the lower incomplete (unregularized) beta function
B(a,b,x) = int(t^(a-1)*(1-t)^(b-1),t=0..x) for a > 0, b > 0, 1 >= x >= 0
where a is the first beta parameter, b is the second beta parameter, and
x is the upper limit of the integralComputes the regularized lower incomplete beta function
I_x(a,b) = 1/Beta(a,b) * int(t^(a-1)*(1-t)^(b-1), t=0..x)
a > 0, b > 0, 1 >= x >= 0 where a is the first beta parameter,
b is the second beta parameter, and x is the upper limit of the
integral.Computes the beta function
where
a is the first beta parameter
and b is the second beta parameter.Computes the lower incomplete (unregularized) beta function
B(a,b,x) = int(t^(a-1)*(1-t)^(b-1),t=0..x) for a > 0, b > 0, 1 >= x >= 0
where a is the first beta parameter, b is the second beta parameter, and
x is the upper limit of the integralComputes the regularized lower incomplete beta function
I_x(a,b) = 1/Beta(a,b) * int(t^(a-1)*(1-t)^(b-1), t=0..x)
a > 0, b > 0, 1 >= x >= 0 where a is the first beta parameter,
b is the second beta parameter, and x is the upper limit of the
integral.Computes the lower incomplete gamma function
gamma(a,x) = int(exp(-t)t^(a-1), t=0..x) for a > 0, x > 0
where a is the argument for the gamma function and x
is the upper integral limit.Computes the lower incomplete regularized gamma function
P(a,x) = 1 / Gamma(a) * int(exp(-t)t^(a-1), t=0..x) for real a > 0, x > 0
where a is the argument for the gamma function and x is the upper
integral limit.Computes the upper incomplete gamma function
Gamma(a,x) = int(exp(-t)t^(a-1), t=0..x) for a > 0, x > 0
where a is the argument for the gamma function and
x is the lower intergral limit.Computes the upper incomplete regularized gamma function
Q(a,x) = 1 / Gamma(a) * int(exp(-t)t^(a-1), t=0..x) for a > 0, x > 0
where a is the argument for the gamma function and
x is the lower integral limit.Computes the natural logarithm
of the beta function
where
a is the first beta parameter
and b is the second beta parameter
and a > 0, b > 0.Computes the Digamma function which is defined as the derivative of
the log of the gamma function. The implementation is based on
“Algorithm AS 103”, Jose Bernardo, Applied Statistics, Volume 25, Number 3
1976, pages 315 - 317
erf calculates the error function at x.erf_inv calculates the inverse error function
at x.erfc calculates the complementary error function
at x.erfc_inv calculates the complementary inverse
error function at x.Computes the gamma function with an accuracy
of 16 floating point digits. The implementation
is derived from “An Analysis of the Lanczos Gamma Approximation”,
Glendon Ralph Pugh, 2004 p. 116
Computes the lower incomplete gamma function
gamma(a,x) = int(exp(-t)t^(a-1), t=0..x) for a > 0, x > 0
where a is the argument for the gamma function and x
is the upper integral limit.Computes the lower incomplete regularized gamma function
P(a,x) = 1 / Gamma(a) * int(exp(-t)t^(a-1), t=0..x) for real a > 0, x > 0
where a is the argument for the gamma function and x is the upper
integral limit.Computes the upper incomplete gamma function
Gamma(a,x) = int(exp(-t)t^(a-1), t=0..x) for a > 0, x > 0
where a is the argument for the gamma function and
x is the lower intergral limit.Computes the upper incomplete regularized gamma function
Q(a,x) = 1 / Gamma(a) * int(exp(-t)t^(a-1), t=0..x) for a > 0, x > 0
where a is the argument for the gamma function and
x is the lower integral limit.Computes the generalized harmonic number of order
n of m
e.g. (1 + 1/2^m + 1/3^m + ... + 1/n^m)Computes the
t-th harmonic numberComputes the natural logarithm
of the beta function
where
a is the first beta parameter
and b is the second beta parameter
and a > 0, b > 0.Computes the logarithm of the gamma function
with an accuracy of 16 floating point digits.
The implementation is derived from
“An Analysis of the Lanczos Gamma Approximation”,
Glendon Ralph Pugh, 2004 p. 116