The cl-randist Reference Manual

This is the cl-randist Reference Manual, version 0.4.2, generated automatically by Declt version 4.0 beta 2 "William Riker" on Sat Dec 03 20:34:58 2022 GMT+0.

Table of Contents


1 Introduction


2 Systems

The main system appears first, followed by any subsystem dependency.


2.1 cl-randist

Random Distribution Generation

Author

Leonardo Varuzza <>

License

BSD except the optional jmt.lisp file

Version

0.4.2

Source

cl-randist.asd.

Child Components

3 Files

Files are sorted by type and then listed depth-first from the systems components trees.


3.1 Lisp


3.1.1 cl-randist/cl-randist.asd

Source

cl-randist.asd.

Parent Component

cl-randist (system).

ASDF Systems

cl-randist.

Packages

cl-randist-system.


3.1.2 cl-randist/packages.lisp

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Packages

random-distributions.


3.1.3 cl-randist/jmt.lisp

Dependency

packages.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface
Internals

3.1.4 cl-randist/randist.lisp

Dependency

jmt.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface
Internals

3.1.5 cl-randist/normal.lisp

Dependency

randist.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface
Internals

3.1.6 cl-randist/gamma.lisp

Dependency

normal.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface
Internals

3.1.7 cl-randist/dirichlet.lisp

Dependency

gamma.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Internals

random-dirichlet1 (function).


3.1.8 cl-randist/beta.lisp

Dependency

dirichlet.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

random-beta (function).


3.1.9 cl-randist/binomial.lisp

Dependency

beta.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

random-binomial (function).


3.1.10 cl-randist/poisson.lisp

Dependency

binomial.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

random-poisson (function).


3.1.11 cl-randist/nbinomial.lisp

Dependency

poisson.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

random-negative-binomial (function).


3.1.12 cl-randist/multinomial.lisp

Dependency

nbinomial.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface
Internals

3.1.13 cl-randist/alias_method.lisp

Dependency

multinomial.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

make-discrete-random-var (function).

Internals

3.1.14 cl-randist/exponential.lisp

Dependency

alias_method.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

random-exponential (function).


3.1.15 cl-randist/f.lisp

Dependency

exponential.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

random-f (function).


3.1.16 cl-randist/pareto.lisp

Dependency

f.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

random-pareto (function).


3.1.17 cl-randist/chisq.lisp

Dependency

pareto.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

random-chi-square (function).


3.1.18 cl-randist/t.lisp

Dependency

chisq.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Internals

3.1.19 cl-randist/cut-point.lisp

Dependency

t.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface

make-discrete-monotone-random-var (function).

Internals

setup-cut-point-randist (function).


3.1.20 cl-randist/desc-stat.lisp

Dependency

cut-point.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Internals

3.1.21 cl-randist/GIG.lisp

Dependency

desc-stat.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Public Interface
Internals

3.1.22 cl-randist/tests.lisp

Dependency

gig.lisp (file).

Source

cl-randist.asd.

Parent Component

cl-randist (system).

Internals

4 Packages

Packages are listed by definition order.


4.1 cl-randist-system

Source

cl-randist.asd.

Use List
  • asdf/interface.
  • common-lisp.

4.2 random-distributions

Source

packages.lisp.

Nicknames
  • cl-randist
  • randist
Use List

common-lisp.

Public Interface
Internals

5 Definitions

Definitions are sorted by export status, category, package, and then by lexicographic order.


5.1 Public Interface


5.1.1 Special variables

Special Variable: *mt-random-state*

Unlike the reference implementation, we’ll initialize the random state to a hopefully somewhat random & unique value.

Package

random-distributions.

Source

jmt.lisp.


5.1.2 Ordinary functions

Function: make-discrete-monotone-random-var (p)
Package

random-distributions.

Source

cut-point.lisp.

Function: make-discrete-random-var (probabilities &optional values)

The function MAKE-DISCRETE-RANDOM-VAR takes an array of probabilities and an (optional) array of values. Produces a function which returns each of the values with the specified probability (or the corresponding integer no values have been given).

Package

random-distributions.

Source

alias_method.lisp.

Function: make-mt-random-state (&optional state)

Analogous to Common Lisp’s MAKE-RANDOM-STATE except that this function works on random states for JMT’s Mersenne Twister implementation.

Optional state argument is interpreted as follows:
if T – make a new random state.
if NIL – return a copy of the current value of *MT-RANDOM-STATE* if an integer – return a random state created by expanding the integer to a full random state
if a list or array – create a new random state object using a copy of that sequence. CF MT-INTERNAL-MAKE-RANDOM-STATE
if a random state – return a copy of the input state.

AJR-comment: this version is better for statistical computations, since it can be used by an externally defined seed. However, it must be optimized, being the core of any pseudo-stochastic algorithm.

Package

random-distributions.

Source

jmt.lisp.

Function: make-random-variable-gig (lambda chi psi)
Package

random-distributions.

Source

gig.lisp.

Function: make-random-variable-gig-poisson (lambda chi psi)
Package

random-distributions.

Source

gig.lisp.

Function: random-bernoulli (p)
Package

random-distributions.

Source

randist.lisp.

Function: random-beta (a b)

The beta distribution has the form

p(x) dx = (Gamma(a + b)/(Gamma(a) Gamma(b))) x^(a-1) (1-x)^(b-1) dx

The method used here is the one described in Knuth

Package

random-distributions.

Source

beta.lisp.

Function: random-binomial (p n)

The binomial distribution has the form,

prob(k) = n!/(k!(n-k)!) * p^k (1-p)^(n-k) for k = 0, 1, ..., n

This is the algorithm from Knuth

Package

random-distributions.

Source

binomial.lisp.

Function: random-chi-square (nu)

Generate random variable for chi square distribution:

p(x) dx = (1/(2*Gamma(nu/2))) (x/2)^(nu/2 - 1) exp(-x/2) dx

Package

random-distributions.

Source

chisq.lisp.

Function: random-exponential (mu)

Random values for: p(x) dx = exp(-x/mu) dx/mu

Package

random-distributions.

Source

exponential.lisp.

Function: random-f (nu1 nu2)

Random value for:

p(x) dx = (nu1^(nu1/2) nu2^(nu2/2) Gamma((nu1 + nu2)/2) / Gamma(nu1/2) Gamma(nu2/2)) *
x^(nu1/2 - 1) (nu2 + nu1 * x)^(-nu1/2 -nu2/2) dx

Package

random-distributions.

Source

f.lisp.

Function: random-gamma (a &optional b)

[syntax suggar] Generate a random variable with gamma distribution using the MT method (see random-gamma-mt)

Package

random-distributions.

Source

gamma.lisp.

Function: random-gamma-int (a)

Random variable with gamma distribution with integer parameter.

Package

random-distributions.

Source

gamma.lisp.

Function: random-gamma-mt (a b)

New version based on Marsaglia and Tsang, ’A Simple Method for generating gamma variables’, ACM Transactions on Mathematical Software, Vol 26, No 3 (2000), p363-372.

Package

random-distributions.

Source

gamma.lisp.

Function: random-gamma1 (a b)

The Gamma distribution of order a>0 is defined by:

p(x) dx = {1 / Gamma(a) b^a } x^{a-1} e^{-x/b} dx

for x>0. If X and Y are independent gamma-distributed random variables of order a1 and a2 with the same scale parameter b, then X+Y has gamma distribution of order a1+a2.

The algorithms below are from Knuth, vol 2, 2nd ed, p. 129.

Works only if a > 1, and is most efficient if a is large

This algorithm, reported in Knuth, is attributed to Ahrens. A faster one, we are told, can be found in: J. H. Ahrens and
U. Dieter, Computing 12 (1974) 223-246.

Package

random-distributions.

Source

gamma.lisp.

Function: random-gig (lambda chi psi)

Random Generalized Inverse Poisson

The algorithm is based on that given by Dagpunar (1989)

Package

random-distributions.

Source

gig.lisp.

Function: random-gig-iid (n lambda chi psi)

Random Generalized Inverse Poisson (vector version)

Package

random-distributions.

Source

gig.lisp.

Function: random-mt (n &optional state)

There is a bit of optimization to do...

Package

random-distributions.

Source

jmt.lisp.

Function: random-multinomial (nn p)
Package

random-distributions.

Source

multinomial.lisp.

Function: random-multinomial% (nn p)

The multinomial distribution has the form

N! n_1 n_2 n_K prob(n_1, n_2, ... n_K) = ——————– p_1 p_2 ... p_K (n_1! n_2! ... n_K!)

where n_1, n_2, ... n_K are nonnegative integers, sum_{k=1,K} n_k = N, and p = (p_1, p_2, ..., p_K) is a probability distribution.

Random variates are generated using the conditional binomial method. This scales well with N and does not require a setup step.

Ref:
C.S. David, The computer generation of multinomial random variates, Comp. Stat. Data Anal. 16 (1993) 205-217

Package

random-distributions.

Source

multinomial.lisp.

Function: random-negative-binomial (p n)

The negative binomial distribution has the form,
prob(k) = Gamma(n + k)/(Gamma(n) Gamma(k + 1)) p^n (1-p)^k for k = 0, 1, ... . Note that n does not have to be an integer. This is the Leger’s algorithm (given in the answers in Knuth)

Package

random-distributions.

Source

nbinomial.lisp.

Function: random-normal (&optional mean sigma)

Generate random variable with normal distribution using ziggurat method

Package

random-distributions.

Source

normal.lisp.

Function: random-normal-bivariate (sigma-x sigma-y &key rho error-limit)

Return a pair of numbers with specific correlation coefficent rho and with specified variances sigma-x and sigma-y; a direct port of gsl_ran_bivariate_gaussian from the GNU Scientific Library:

void
gsl_ran_bivariate_gaussian (const gsl_rng * r,
double sigma_x, double sigma_y, double rho, double *x, double *y)
{
double u, v, r2, scale;

do
{
/* choose x,y in uniform square (-1,-1) to (+1,+1) */

u = -1 + 2 * gsl_rng_uniform (r);
v = -1 + 2 * gsl_rng_uniform (r);

/* see if it is in the unit circle */
r2 = u * u + v * v;
}
while (r2 > 1.0 || r2 == 0);

scale = sqrt (-2.0 * log (r2) / r2);

*x = sigma_x * u * scale;
*y = sigma_y * (rho * u + sqrt(1 - rho*rho) * v) * scale;
}

I need a good test for this one.

Package

random-distributions.

Source

normal.lisp.

Function: random-normal-ziggurat (mean sigma)

This routine is based on the following article, with a couple of modifications which simplify the implementation.

George Marsaglia, Wai Wan Tsang
The Ziggurat Method for Generating Random Variables
Journal of Statistical Software, vol. 5 (2000), no. 8 http://www.jstatsoft.org/v05/i08/

The modifications are:

1) use 128 steps instead of 256 to decrease the amount of static data necessary.

2) use an acceptance sampling from an exponential wedge exp(-R*(x-R/2)) for the tail of the base strip to simplify the implementation. The area of exponential wedge is used in calculating ’v’ and the coefficients in ziggurat table, so the coefficients differ slightly from those in the Marsaglia and Tsang paper.

See also Leong et al, ’A Comment on the Implementation of the Ziggurat Method’, Journal of Statistical Software, vol 5 (2005), no 7.

Package

random-distributions.

Source

normal.lisp.

Function: random-pareto (a b)

Random value for parato distribution:
p(x) dx = (a/b) / (x/b)^(a+1) dx for x >= b

Package

random-distributions.

Source

pareto.lisp.

Function: random-poisson (mu)

The poisson distribution has the form

p(n) = (mu^n / n!) exp(-mu)

for n = 0, 1, 2, ... . The method used here is the one from Knuth.

Package

random-distributions.

Source

poisson.lisp.

Function: random-uniform ()

[syntax suggar] Random variable with uniform distribution in interval [0,1)

Package

random-distributions.

Source

randist.lisp.


5.1.3 Standalone methods

Method: make-load-form ((obj mt-random-state) &optional environment)
Source

jmt.lisp.

Method: print-object ((obj mt-random-state) stream)
Source

jmt.lisp.


5.2 Internals


5.2.1 Constants

Constant: +e+
Package

random-distributions.

Source

gamma.lisp.

Constant: +mt-k-inverse-2^32f+

1/(2^32), as a floating-point number

Package

random-distributions.

Source

jmt.lisp.

Constant: +mt-k2^32+
Package

random-distributions.

Source

jmt.lisp.

Constant: +mt-lower-mask+

least significant r bits

Package

random-distributions.

Source

jmt.lisp.

Constant: +mt-m+
Package

random-distributions.

Source

jmt.lisp.

Constant: +mt-n+
Package

random-distributions.

Source

jmt.lisp.

Constant: +mt-tempering-mask-b+
Package

random-distributions.

Source

jmt.lisp.

Constant: +mt-tempering-mask-c+
Package

random-distributions.

Source

jmt.lisp.

Constant: +mt-upper-mask+

most significant w-r bits

Package

random-distributions.

Source

jmt.lisp.

Constant: +r+
Package

random-distributions.

Source

normal.lisp.


5.2.2 Special variables

Special Variable: *ktab*
Package

random-distributions.

Source

normal.lisp.

Special Variable: *n*
Package

random-distributions.

Source

tests.lisp.

Special Variable: *wtab*
Package

random-distributions.

Source

normal.lisp.

Special Variable: *ytab*
Package

random-distributions.

Source

normal.lisp.


5.2.3 Macros

Macro: sd (&rest args)
Package

random-distributions.

Source

desc-stat.lisp.

Macro: var (&rest args)
Package

random-distributions.

Source

desc-stat.lisp.


5.2.4 Ordinary functions

Function: %random-gig (l1 alpha beta m a b c)
Package

random-distributions.

Source

gig.lisp.

Function: coefficient-of-variation (sequence)
Package

random-distributions.

Source

desc-stat.lisp.

Function: convert-to-double-float-vector (x)
Package

random-distributions.

Source

multinomial.lisp.

Function: copy-mt-random-state (instance)
Package

random-distributions.

Source

jmt.lisp.

Function: create-alias-method-vectors (probabilities)
Package

random-distributions.

Source

alias_method.lisp.

Function: gamma-frac (a)
Package

random-distributions.

Source

gamma.lisp.

Function: gamma-large (a)
Package

random-distributions.

Source

gamma.lisp.

Function: gen-uniform (&optional n)
Package

random-distributions.

Source

tests.lisp.

Function: genlist (f n)
Package

random-distributions.

Source

tests.lisp.

Function: geometric-mean (sequence &optional base)
Package

random-distributions.

Source

desc-stat.lisp.

Function: gig-setup (lambda chi psi)
Package

random-distributions.

Source

gig.lisp.

Function: mean (sequence)
Package

random-distributions.

Source

desc-stat.lisp.

Function: median (sequence)
Package

random-distributions.

Source

desc-stat.lisp.

Function: mode (sequence)
Package

random-distributions.

Source

desc-stat.lisp.

Function: mt-genrand ()
Package

random-distributions.

Source

jmt.lisp.

Function: mt-internal-make-random-state (&key mti arr)
Package

random-distributions.

Source

jmt.lisp.

Function: mt-make-random-state-integer (n)

Use the single integer to expand into a bunch of
integers to use as an MT-RANDOM-STATE.
Copied from the ’sgenrand’ function in mt19937int.c.
This is mostly an internal function. I recommend using MAKE-MT-RANDOM-STATE unless specific circumstances dictate otherwise.

Package

random-distributions.

Source

jmt.lisp.

Function: mt-make-random-state-random ()

Generate a new random state from a new, hopefully somewhat random, value.
This is mostly an internal function. I recommend using MAKE-MT-RANDOM-STATE unless specific circumstances dictate otherwise.

Package

random-distributions.

Source

jmt.lisp.

Reader: mt-random-state-arr (instance)
Writer: (setf mt-random-state-arr) (instance)
Package

random-distributions.

Source

jmt.lisp.

Target Slot

arr.

Reader: mt-random-state-mti (instance)
Writer: (setf mt-random-state-mti) (instance)
Package

random-distributions.

Source

jmt.lisp.

Target Slot

mti.

Function: mt-random-state-p (object)
Package

random-distributions.

Source

jmt.lisp.

Function: mt-refill ()

In the C program mt19937int.c, there is a function called ’genrand’, & in that function there is a block of code to execute when the mt[] array is exhausted. This function is that block of code. I’ve removed it from my MT-GENRAND function for clarity.

Package

random-distributions.

Source

jmt.lisp.

Function: mt-tempering-shift-l (n)
Package

random-distributions.

Source

jmt.lisp.

Function: mt-tempering-shift-s (n)
Package

random-distributions.

Source

jmt.lisp.

Function: mt-tempering-shift-t (n)
Package

random-distributions.

Source

jmt.lisp.

Function: mt-tempering-shift-u (n)
Package

random-distributions.

Source

jmt.lisp.

Function: percentile (sequence percent)
Package

random-distributions.

Source

desc-stat.lisp.

Function: profile-gamma (&optional n)
Package

random-distributions.

Source

tests.lisp.

Function: random-dirichlet1 (alpha theta)
Package

random-distributions.

Source

dirichlet.lisp.

Function: random-generalized-inverse-poisson (lambda chi psi)
Package

random-distributions.

Source

gig.lisp.

Function: random-multinomial1 (nn p n)

Return the genrated values in the n vector

Package

random-distributions.

Source

multinomial.lisp.

Function: random-pos ()

Create the sign, i.e. random positive or negative, similar to a binary result.

Package

random-distributions.

Source

randist.lisp.

Function: random-t (nu)
Package

random-distributions.

Source

t.lisp.

Function: random-t-nu<=2 (nu)
Package

random-distributions.

Source

t.lisp.

Function: random-t-nu>2 (nu)
Package

random-distributions.

Source

t.lisp.

Function: random-uniform-jmt ()

[syntax suggar] Random variable with uniform distribution in interval [0,1)

Package

random-distributions.

Source

randist.lisp.

Function: random-vector-iid (n variable)

Return a vector with n IID instances of variable

Package

random-distributions.

Source

randist.lisp.

Function: range (sequence)
Package

random-distributions.

Source

desc-stat.lisp.

Function: report-uniform-count (c n)
Package

random-distributions.

Source

alias_method.lisp.

Function: setup-cut-point-randist (p)
Package

random-distributions.

Source

cut-point.lisp.

Function: square (x)
Package

random-distributions.

Source

desc-stat.lisp.

Function: standard-deviation (sequence)
Package

random-distributions.

Source

desc-stat.lisp.

Function: standard-error-of-the-mean (sequence)
Package

random-distributions.

Source

desc-stat.lisp.

Function: test-alias-method (n runs)
Package

random-distributions.

Source

alias_method.lisp.

Function: test-alias-method-uniform (n)
Package

random-distributions.

Source

alias_method.lisp.

Function: test-alias-method-zeros ()
Package

random-distributions.

Source

alias_method.lisp.

Function: test-binomial (&optional n)
Package

random-distributions.

Source

tests.lisp.

Function: test-dist (f &optional n)
Package

random-distributions.

Source

tests.lisp.

Function: test-gamma-mt-speed (&optional n)
Package

random-distributions.

Source

tests.lisp.

Function: test-gamma-speed (&optional n)
Package

random-distributions.

Source

tests.lisp.

Function: test-gig-range ()
Package

random-distributions.

Source

gig.lisp.

Function: test-gig-speed ()
Package

random-distributions.

Source

gig.lisp.

Function: test-multinomial (&optional k)
Package

random-distributions.

Source

multinomial.lisp.

Function: test-multinomial1 (nn p &optional k)
Package

random-distributions.

Source

multinomial.lisp.

Function: test-random-uniform-jmt (&optional n)
Package

random-distributions.

Source

tests.lisp.

Function: test-zigg-speed (&optional n)
Package

random-distributions.

Source

tests.lisp.

Function: transfer-sign (a b)
Package

random-distributions.

Source

gig.lisp.

Function: uniform-reference (n)
Package

random-distributions.

Source

alias_method.lisp.

Function: variance (sequence)
Package

random-distributions.

Source

desc-stat.lisp.

Function: zeroin (ax bx fun &optional tol)

zero of the function f(x) is computed in the interval ax,bx .

input..

ax left endpoint of initial interval
bx right endpoint of initial interval
f function subprogram which evaluates f(x) for any x in
the interval ax,bx
tol desired length of the interval of uncertainty of the
final result ( .ge. 0.0d0)

output..

zeroin abcissa approximating a zero of f in the interval ax,bx

it is assumed that f(ax) and f(bx) have opposite signs without a check. zeroin returns a zero x in the given interval ax,bx to within a tolerance 4*macheps*abs(x) + tol, where macheps is the relative machine precision.
this function subprogram is a slightly modified translation of the algol 60 procedure zero given in richard brent, algorithms for minimization without derivatives, prentice - hall, inc. (1973).

Package

random-distributions.

Source

gig.lisp.


5.2.5 Structures

Structure: mt-random-state
Package

random-distributions.

Source

jmt.lisp.

Direct superclasses

structure-object.

Direct methods
Direct slots
Slot: mti
Type

(unsigned-byte 32)

Initform

0

Readers

mt-random-state-mti.

Writers

(setf mt-random-state-mti).

Slot: arr
Type

(simple-array (unsigned-byte 32))

Initform

(error "unsupplied.")

Readers

mt-random-state-arr.

Writers

(setf mt-random-state-arr).


Appendix A Indexes


A.1 Concepts


A.2 Functions

Jump to:   %   (  
C   F   G   M   P   R   S   T   U   V   Z  
Index Entry  Section

%
%random-gig: Private ordinary functions

(
(setf mt-random-state-arr): Private ordinary functions
(setf mt-random-state-mti): Private ordinary functions

C
coefficient-of-variation: Private ordinary functions
convert-to-double-float-vector: Private ordinary functions
copy-mt-random-state: Private ordinary functions
create-alias-method-vectors: Private ordinary functions

F
Function, %random-gig: Private ordinary functions
Function, (setf mt-random-state-arr): Private ordinary functions
Function, (setf mt-random-state-mti): Private ordinary functions
Function, coefficient-of-variation: Private ordinary functions
Function, convert-to-double-float-vector: Private ordinary functions
Function, copy-mt-random-state: Private ordinary functions
Function, create-alias-method-vectors: Private ordinary functions
Function, gamma-frac: Private ordinary functions
Function, gamma-large: Private ordinary functions
Function, gen-uniform: Private ordinary functions
Function, genlist: Private ordinary functions
Function, geometric-mean: Private ordinary functions
Function, gig-setup: Private ordinary functions
Function, make-discrete-monotone-random-var: Public ordinary functions
Function, make-discrete-random-var: Public ordinary functions
Function, make-mt-random-state: Public ordinary functions
Function, make-random-variable-gig: Public ordinary functions
Function, make-random-variable-gig-poisson: Public ordinary functions
Function, mean: Private ordinary functions
Function, median: Private ordinary functions
Function, mode: Private ordinary functions
Function, mt-genrand: Private ordinary functions
Function, mt-internal-make-random-state: Private ordinary functions
Function, mt-make-random-state-integer: Private ordinary functions
Function, mt-make-random-state-random: Private ordinary functions
Function, mt-random-state-arr: Private ordinary functions
Function, mt-random-state-mti: Private ordinary functions
Function, mt-random-state-p: Private ordinary functions
Function, mt-refill: Private ordinary functions
Function, mt-tempering-shift-l: Private ordinary functions
Function, mt-tempering-shift-s: Private ordinary functions
Function, mt-tempering-shift-t: Private ordinary functions
Function, mt-tempering-shift-u: Private ordinary functions
Function, percentile: Private ordinary functions
Function, profile-gamma: Private ordinary functions
Function, random-bernoulli: Public ordinary functions
Function, random-beta: Public ordinary functions
Function, random-binomial: Public ordinary functions
Function, random-chi-square: Public ordinary functions
Function, random-dirichlet1: Private ordinary functions
Function, random-exponential: Public ordinary functions
Function, random-f: Public ordinary functions
Function, random-gamma: Public ordinary functions
Function, random-gamma-int: Public ordinary functions
Function, random-gamma-mt: Public ordinary functions
Function, random-gamma1: Public ordinary functions
Function, random-generalized-inverse-poisson: Private ordinary functions
Function, random-gig: Public ordinary functions
Function, random-gig-iid: Public ordinary functions
Function, random-mt: Public ordinary functions
Function, random-multinomial: Public ordinary functions
Function, random-multinomial%: Public ordinary functions
Function, random-multinomial1: Private ordinary functions
Function, random-negative-binomial: Public ordinary functions
Function, random-normal: Public ordinary functions
Function, random-normal-bivariate: Public ordinary functions
Function, random-normal-ziggurat: Public ordinary functions
Function, random-pareto: Public ordinary functions
Function, random-poisson: Public ordinary functions
Function, random-pos: Private ordinary functions
Function, random-t: Private ordinary functions
Function, random-t-nu<=2: Private ordinary functions
Function, random-t-nu>2: Private ordinary functions
Function, random-uniform: Public ordinary functions
Function, random-uniform-jmt: Private ordinary functions
Function, random-vector-iid: Private ordinary functions
Function, range: Private ordinary functions
Function, report-uniform-count: Private ordinary functions
Function, setup-cut-point-randist: Private ordinary functions
Function, square: Private ordinary functions
Function, standard-deviation: Private ordinary functions
Function, standard-error-of-the-mean: Private ordinary functions
Function, test-alias-method: Private ordinary functions
Function, test-alias-method-uniform: Private ordinary functions
Function, test-alias-method-zeros: Private ordinary functions
Function, test-binomial: Private ordinary functions
Function, test-dist: Private ordinary functions
Function, test-gamma-mt-speed: Private ordinary functions
Function, test-gamma-speed: Private ordinary functions
Function, test-gig-range: Private ordinary functions
Function, test-gig-speed: Private ordinary functions
Function, test-multinomial: Private ordinary functions
Function, test-multinomial1: Private ordinary functions
Function, test-random-uniform-jmt: Private ordinary functions
Function, test-zigg-speed: Private ordinary functions
Function, transfer-sign: Private ordinary functions
Function, uniform-reference: Private ordinary functions
Function, variance: Private ordinary functions
Function, zeroin: Private ordinary functions

G
gamma-frac: Private ordinary functions
gamma-large: Private ordinary functions
gen-uniform: Private ordinary functions
genlist: Private ordinary functions
geometric-mean: Private ordinary functions
gig-setup: Private ordinary functions

M
Macro, sd: Private macros
Macro, var: Private macros
make-discrete-monotone-random-var: Public ordinary functions
make-discrete-random-var: Public ordinary functions
make-load-form: Public standalone methods
make-mt-random-state: Public ordinary functions
make-random-variable-gig: Public ordinary functions
make-random-variable-gig-poisson: Public ordinary functions
mean: Private ordinary functions
median: Private ordinary functions
Method, make-load-form: Public standalone methods
Method, print-object: Public standalone methods
mode: Private ordinary functions
mt-genrand: Private ordinary functions
mt-internal-make-random-state: Private ordinary functions
mt-make-random-state-integer: Private ordinary functions
mt-make-random-state-random: Private ordinary functions
mt-random-state-arr: Private ordinary functions
mt-random-state-mti: Private ordinary functions
mt-random-state-p: Private ordinary functions
mt-refill: Private ordinary functions
mt-tempering-shift-l: Private ordinary functions
mt-tempering-shift-s: Private ordinary functions
mt-tempering-shift-t: Private ordinary functions
mt-tempering-shift-u: Private ordinary functions

P
percentile: Private ordinary functions
print-object: Public standalone methods
profile-gamma: Private ordinary functions

R
random-bernoulli: Public ordinary functions
random-beta: Public ordinary functions
random-binomial: Public ordinary functions
random-chi-square: Public ordinary functions
random-dirichlet1: Private ordinary functions
random-exponential: Public ordinary functions
random-f: Public ordinary functions
random-gamma: Public ordinary functions
random-gamma-int: Public ordinary functions
random-gamma-mt: Public ordinary functions
random-gamma1: Public ordinary functions
random-generalized-inverse-poisson: Private ordinary functions
random-gig: Public ordinary functions
random-gig-iid: Public ordinary functions
random-mt: Public ordinary functions
random-multinomial: Public ordinary functions
random-multinomial%: Public ordinary functions
random-multinomial1: Private ordinary functions
random-negative-binomial: Public ordinary functions
random-normal: Public ordinary functions
random-normal-bivariate: Public ordinary functions
random-normal-ziggurat: Public ordinary functions
random-pareto: Public ordinary functions
random-poisson: Public ordinary functions
random-pos: Private ordinary functions
random-t: Private ordinary functions
random-t-nu<=2: Private ordinary functions
random-t-nu>2: Private ordinary functions
random-uniform: Public ordinary functions
random-uniform-jmt: Private ordinary functions
random-vector-iid: Private ordinary functions
range: Private ordinary functions
report-uniform-count: Private ordinary functions

S
sd: Private macros
setup-cut-point-randist: Private ordinary functions
square: Private ordinary functions
standard-deviation: Private ordinary functions
standard-error-of-the-mean: Private ordinary functions

T
test-alias-method: Private ordinary functions
test-alias-method-uniform: Private ordinary functions
test-alias-method-zeros: Private ordinary functions
test-binomial: Private ordinary functions
test-dist: Private ordinary functions
test-gamma-mt-speed: Private ordinary functions
test-gamma-speed: Private ordinary functions
test-gig-range: Private ordinary functions
test-gig-speed: Private ordinary functions
test-multinomial: Private ordinary functions
test-multinomial1: Private ordinary functions
test-random-uniform-jmt: Private ordinary functions
test-zigg-speed: Private ordinary functions
transfer-sign: Private ordinary functions

U
uniform-reference: Private ordinary functions

V
var: Private macros
variance: Private ordinary functions

Z
zeroin: Private ordinary functions


A.3 Variables


A.4 Data types

Jump to:   A   B   C   D   E   F   G   J   M   N   P   R   S   T  
Index Entry  Section

A
alias_method.lisp: The cl-randist/alias_method․lisp file

B
beta.lisp: The cl-randist/beta․lisp file
binomial.lisp: The cl-randist/binomial․lisp file

C
chisq.lisp: The cl-randist/chisq․lisp file
cl-randist: The cl-randist system
cl-randist-system: The cl-randist-system package
cl-randist.asd: The cl-randist/cl-randist․asd file
cut-point.lisp: The cl-randist/cut-point․lisp file

D
desc-stat.lisp: The cl-randist/desc-stat․lisp file
dirichlet.lisp: The cl-randist/dirichlet․lisp file

E
exponential.lisp: The cl-randist/exponential․lisp file

F
f.lisp: The cl-randist/f․lisp file
File, alias_method.lisp: The cl-randist/alias_method․lisp file
File, beta.lisp: The cl-randist/beta․lisp file
File, binomial.lisp: The cl-randist/binomial․lisp file
File, chisq.lisp: The cl-randist/chisq․lisp file
File, cl-randist.asd: The cl-randist/cl-randist․asd file
File, cut-point.lisp: The cl-randist/cut-point․lisp file
File, desc-stat.lisp: The cl-randist/desc-stat․lisp file
File, dirichlet.lisp: The cl-randist/dirichlet․lisp file
File, exponential.lisp: The cl-randist/exponential․lisp file
File, f.lisp: The cl-randist/f․lisp file
File, gamma.lisp: The cl-randist/gamma․lisp file
File, gig.lisp: The cl-randist/gig․lisp file
File, jmt.lisp: The cl-randist/jmt․lisp file
File, multinomial.lisp: The cl-randist/multinomial․lisp file
File, nbinomial.lisp: The cl-randist/nbinomial․lisp file
File, normal.lisp: The cl-randist/normal․lisp file
File, packages.lisp: The cl-randist/packages․lisp file
File, pareto.lisp: The cl-randist/pareto․lisp file
File, poisson.lisp: The cl-randist/poisson․lisp file
File, randist.lisp: The cl-randist/randist․lisp file
File, t.lisp: The cl-randist/t․lisp file
File, tests.lisp: The cl-randist/tests․lisp file

G
gamma.lisp: The cl-randist/gamma․lisp file
gig.lisp: The cl-randist/gig․lisp file

J
jmt.lisp: The cl-randist/jmt․lisp file

M
mt-random-state: Private structures
multinomial.lisp: The cl-randist/multinomial․lisp file

N
nbinomial.lisp: The cl-randist/nbinomial․lisp file
normal.lisp: The cl-randist/normal․lisp file

P
Package, cl-randist-system: The cl-randist-system package
Package, random-distributions: The random-distributions package
packages.lisp: The cl-randist/packages․lisp file
pareto.lisp: The cl-randist/pareto․lisp file
poisson.lisp: The cl-randist/poisson․lisp file

R
randist.lisp: The cl-randist/randist․lisp file
random-distributions: The random-distributions package

S
Structure, mt-random-state: Private structures
System, cl-randist: The cl-randist system

T
t.lisp: The cl-randist/t․lisp file
tests.lisp: The cl-randist/tests․lisp file