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Chapter Contents
Chapter Introduction
NAG Toolbox

NAG Toolbox: nag_rand_int_general (g05td)


    1  Purpose
    2  Syntax
    7  Accuracy
    9  Example


nag_rand_int_general (g05td) generates a vector of pseudorandom integers from a discrete distribution with a given PDF (probability density function) or CDF (cumulative distribution function) p.


[r, state, x, ifail] = g05td(mode, n, p, ip1, itype, r, state, 'np', np)
[r, state, x, ifail] = nag_rand_int_general(mode, n, p, ip1, itype, r, state, 'np', np)


nag_rand_int_general (g05td) generates a sequence of n integers xi, from a discrete distribution defined by information supplied in p. This may either be the PDF or CDF of the distribution. A reference vector is first set up to contain the CDF of the distribution in its higher elements, followed by an index.
Setting up the reference vector and subsequent generation of variates can each be performed by separate calls to nag_rand_int_general (g05td) or may be combined in a single call.
One of the initialization functions nag_rand_init_repeat (g05kf) (for a repeatable sequence if computed sequentially) or nag_rand_init_nonrepeat (g05kg) (for a non-repeatable sequence) must be called prior to the first call to nag_rand_int_general (g05td).


Kendall M G and Stuart A (1969) The Advanced Theory of Statistics (Volume 1) (3rd Edition) Griffin
Knuth D E (1981) The Art of Computer Programming (Volume 2) (2nd Edition) Addison–Wesley


Compulsory Input Parameters

1:     mode int64int32nag_int scalar
A code for selecting the operation to be performed by the function.
Set up reference vector only.
Generate variates using reference vector set up in a prior call to nag_rand_int_general (g05td).
Set up reference vector and generate variates.
Generate variates without using the reference vector.
Constraint: mode=0, 1, 2 or 3.
2:     n int64int32nag_int scalar
n, the number of pseudorandom numbers to be generated.
Constraint: n0.
3:     pnp – double array
The PDF or CDF of the distribution.
  • 0.0pi1.0, for i=1,2,,np;
  • if itype=1, i=1 np pi=1.0;
  • if itype=2, pi<pj, ​i<j​ and ​pnp=1.0.
4:     ip1 int64int32nag_int scalar
The value of the variate, a whole number, to which the probability in p1 corresponds.
5:     itype int64int32nag_int scalar
Indicates the type of information contained in p.
p contains a probability distribution function (PDF).
p contains a cumulative distribution function (CDF).
Constraint: itype=1 or 2.
6:     rlr – double array
lr, the dimension of the array, must satisfy the constraint
  • if mode=0 or 2, lrnp+8;
  • if mode=1, lr should remain unchanged from the previous call to nag_rand_int_general (g05td).
If mode=1, the reference vector from the previous call to nag_rand_int_general (g05td).
7:     state: int64int32nag_int array
Note: the actual argument supplied must be the array state supplied to the initialization routines nag_rand_init_repeat (g05kf) or nag_rand_init_nonrepeat (g05kg).
Contains information on the selected base generator and its current state.

Optional Input Parameters

1:     np int64int32nag_int scalar
Default: the dimension of the array p.
The number of values supplied in p defining the PDF or CDF of the discrete distribution.
Constraint: np>0.

Output Parameters

1:     rlr – double array
The reference vector.
2:     state: int64int32nag_int array
Contains updated information on the state of the generator.
3:     xn int64int32nag_int array
Contains n pseudorandom numbers from the specified discrete distribution.
4:     ifail int64int32nag_int scalar
ifail=0 unless the function detects an error (see Error Indicators and Warnings).

Error Indicators and Warnings

Errors or warnings detected by the function:
Constraint: mode=0, 1 or 2.
Constraint: n0.
Constraint: if itype=2, pnp=1.0.
On entry, at least one element of the vector p is less than 0.0 or greater than 1.0.
On entry, itype=1 and the sum of the elements of p do not equal one.
On entry, itype=2 and the values of p are not all in stricly ascending order.
Constraint: np>0.
Constraint: itype=1 or 2.
On entry, some of the elements of the array r have been corrupted or have not been initialized.
The value of np or ip1 is not the same as when r was set up in a previous call.
On entry, lr is too small when mode=0 or 2.
On entry, state vector has been corrupted or not initialized.
An unexpected error has been triggered by this routine. Please contact NAG.
Your licence key may have expired or may not have been installed correctly.
Dynamic memory allocation failed.


Not applicable.

Further Comments



This example prints 20 pseudorandom variates from a discrete distribution whose PDF, p, is defined as follows:
n p -5 0.01 -4 0.02 -3 0.04 -2 0.08 -1 0.20 -0 0.30 -1 0.20 -2 0.08 -3 0.04 -4 0.02 -5 0.01  
The reference vector is set up and and the variates are generated by a single call to nag_rand_int_general (g05td), after initialization by nag_rand_init_repeat (g05kf).
function g05td_example

fprintf('g05td example results\n\n');

% Initialize the base generator to a repeatable sequence
seed  = [int64(1762543)];
genid = int64(1);
subid = int64(1);
[state, ifail] = g05kf( ...
                        genid, subid, seed);

% Number of variates
n = int64(20);

% Parameters (PDF) 
p = [0.01;     0.02;     0.04;    0.08;     0.2;     0.3;
     0.2;      0.08;     0.04;    0.02;     0.01];
ip1 = int64(-5);
itype = int64(1);

% Generate variates from PDF defined by p and ip1
mode = int64(2);
r = zeros(60, 1);
[r, state, x, ifail] = g05td( ...
                              mode, n, p, ip1, itype, r, state);


g05td example results


PDF version (NAG web site, 64-bit version, 64-bit version)
Chapter Contents
Chapter Introduction
NAG Toolbox

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