# NAG FL Interfaceg05taf (int_​binomial)

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## 1Purpose

g05taf generates a vector of pseudorandom integers from the discrete binomial distribution with parameters $m$ and $p$.

## 2Specification

Fortran Interface
 Subroutine g05taf ( mode, n, m, p, r, lr, x,
 Integer, Intent (In) :: mode, n, m, lr Integer, Intent (Inout) :: state(*), ifail Integer, Intent (Out) :: x(n) Real (Kind=nag_wp), Intent (In) :: p Real (Kind=nag_wp), Intent (Inout) :: r(lr)
#include <nag.h>
 void g05taf_ (const Integer *mode, const Integer *n, const Integer *m, const double *p, double r[], const Integer *lr, Integer state[], Integer x[], Integer *ifail)
The routine may be called by the names g05taf or nagf_rand_int_binomial.

## 3Description

g05taf generates $n$ integers ${x}_{i}$ from a discrete binomial distribution, where the probability of ${x}_{i}=I$ is
 $P(xi=I)= m! I!(m-I)! ⁢ pI×(1-p)m-I, I=0,1,…,m,$
where $m\ge 0$ and $0\le p\le 1$. This represents the probability of achieving $I$ successes in $m$ trials when the probability of success at a single trial is $p$.
The variates can be generated with or without using a search table and index. If a search table is used then it is stored with the index in a reference vector and subsequent calls to g05taf with the same parameter values can then use this reference vector to generate further variates.
One of the initialization routines g05kff (for a repeatable sequence if computed sequentially) or g05kgf (for a non-repeatable sequence) must be called prior to the first call to g05taf.

## 4References

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

## 5Arguments

1: $\mathbf{mode}$Integer Input
On entry: a code for selecting the operation to be performed by the routine.
${\mathbf{mode}}=0$
Set up reference vector only.
${\mathbf{mode}}=1$
Generate variates using reference vector set up in a prior call to g05taf.
${\mathbf{mode}}=2$
Set up reference vector and generate variates.
${\mathbf{mode}}=3$
Generate variates without using the reference vector.
Constraint: ${\mathbf{mode}}=0$, $1$, $2$ or $3$.
2: $\mathbf{n}$Integer Input
On entry: $n$, the number of pseudorandom numbers to be generated.
Constraint: ${\mathbf{n}}\ge 0$.
3: $\mathbf{m}$Integer Input
On entry: $m$, the number of trials of the distribution.
Constraint: ${\mathbf{m}}\ge 0$.
4: $\mathbf{p}$Real (Kind=nag_wp) Input
On entry: $p$, the probability of success of the binomial distribution.
Constraint: $0.0\le {\mathbf{p}}\le 1.0$.
5: $\mathbf{r}\left({\mathbf{lr}}\right)$Real (Kind=nag_wp) array Communication Array
On entry: if ${\mathbf{mode}}=1$, the reference vector from the previous call to g05taf.
If ${\mathbf{mode}}=3$, r is not referenced.
On exit: if ${\mathbf{mode}}\ne 3$, the reference vector.
6: $\mathbf{lr}$Integer Input
On entry: the dimension of the array r as declared in the (sub)program from which g05taf is called.
Suggested values:
• if ${\mathbf{mode}}\ne 3$, ${\mathbf{lr}}=22+20×\sqrt{{\mathbf{m}}×{\mathbf{p}}×\left(1-{\mathbf{p}}\right)}$;
• otherwise ${\mathbf{lr}}=1$.
Constraints:
• if ${\mathbf{mode}}=0$ or $2$,
$\begin{array}{lll}{\mathbf{lr}}& >& \mathrm{min}\phantom{\rule{0.125em}{0ex}}\left({\mathbf{m}},\mathrm{int}\left[{\mathbf{m}}×{\mathbf{p}}+7.15×\sqrt{{\mathbf{m}}×{\mathbf{p}}×\left(1-{\mathbf{p}}\right)}+1\right]\right)\\ & & -\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(0,\mathrm{int}\left[{\mathbf{m}}×{\mathbf{p}}-7.15×\sqrt{{\mathbf{m}}×{\mathbf{p}}×\left(1-{\mathbf{p}}\right)}-7.15\right]\right)+8\end{array}$;
• if ${\mathbf{mode}}=1$, lr must remain unchanged from the previous call to g05taf.
7: $\mathbf{state}\left(*\right)$Integer array Communication Array
Note: the actual argument supplied must be the array state supplied to the initialization routines g05kff or g05kgf.
On entry: contains information on the selected base generator and its current state.
On exit: contains updated information on the state of the generator.
8: $\mathbf{x}\left({\mathbf{n}}\right)$Integer array Output
On exit: the $n$ pseudorandom numbers from the specified binomial distribution.
9: $\mathbf{ifail}$Integer Input/Output
On entry: ifail must be set to $0$, $-1$ or $1$ to set behaviour on detection of an error; these values have no effect when no error is detected.
A value of $0$ causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of $-1$ means that an error message is printed while a value of $1$ means that it is not.
If halting is not appropriate, the value $-1$ or $1$ is recommended. If message printing is undesirable, then the value $1$ is recommended. Otherwise, the value $0$ is recommended. When the value $-\mathbf{1}$ or $\mathbf{1}$ is used it is essential to test the value of ifail on exit.
On exit: ${\mathbf{ifail}}={\mathbf{0}}$ unless the routine detects an error or a warning has been flagged (see Section 6).

## 6Error Indicators and Warnings

If on entry ${\mathbf{ifail}}=0$ or $-1$, explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
${\mathbf{ifail}}=1$
On entry, ${\mathbf{mode}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{mode}}=0$, $1$, $2$ or $3$.
${\mathbf{ifail}}=2$
On entry, ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{n}}\ge 0$.
${\mathbf{ifail}}=3$
On entry, ${\mathbf{m}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{m}}\ge 0$.
${\mathbf{ifail}}=4$
On entry, ${\mathbf{p}}=⟨\mathit{\text{value}}⟩$.
Constraint: $0.0\le {\mathbf{p}}\le 1.0$.
${\mathbf{ifail}}=5$
On entry, some of the elements of the array r have been corrupted or have not been initialized.
p or m is not the same as when r was set up in a previous call.
Previous value of ${\mathbf{p}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{p}}=⟨\mathit{\text{value}}⟩$.
Previous value of ${\mathbf{m}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{m}}=⟨\mathit{\text{value}}⟩$.
${\mathbf{ifail}}=6$
On entry, lr is too small when ${\mathbf{mode}}=0$ or $2$: ${\mathbf{lr}}=⟨\mathit{\text{value}}⟩$, minimum length required $\text{}=⟨\mathit{\text{value}}⟩$.
${\mathbf{ifail}}=7$
On entry, state vector has been corrupted or not initialized.
${\mathbf{ifail}}=-99$
See Section 7 in the Introduction to the NAG Library FL Interface for further information.
${\mathbf{ifail}}=-399$
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library FL Interface for further information.
${\mathbf{ifail}}=-999$
Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

Not applicable.

## 8Parallelism and Performance

g05taf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

None.

## 10Example

This example prints $20$ pseudorandom integers from a binomial distribution with parameters $m=6000$ and $p=0.8$, generated by a single call to g05taf, after initialization by g05kff.

### 10.1Program Text

Program Text (g05tafe.f90)

### 10.2Program Data

Program Data (g05tafe.d)

### 10.3Program Results

Program Results (g05tafe.r)