# NAG Library Routine Document

## 1Purpose

g05sff generates a vector of pseudorandom numbers from a (negative) exponential distribution with mean $a$.

## 2Specification

Fortran Interface
 Subroutine g05sff ( n, a, x,
 Integer, Intent (In) :: n Integer, Intent (Inout) :: state(*), ifail Real (Kind=nag_wp), Intent (In) :: a Real (Kind=nag_wp), Intent (Out) :: x(n)
#include nagmk26.h
 void g05sff_ (const Integer *n, const double *a, Integer state[], double x[], Integer *ifail)

## 3Description

The exponential distribution has PDF (probability density function):
 $fx = 1a e -x/a if ​x≥0, fx=0 otherwise.$
g05sff returns the values
 $xi = -a ln⁡yi$
where ${y}_{i}$ are the next $n$ numbers generated by a uniform $\left(0,1\right]$ generator.
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 g05sff.

## 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:     $\mathbf{n}$ – IntegerInput
On entry: $n$, the number of pseudorandom numbers to be generated.
Constraint: ${\mathbf{n}}\ge 0$.
2:     $\mathbf{a}$ – Real (Kind=nag_wp)Input
On entry: $a$, the mean of the distribution.
Constraint: ${\mathbf{a}}>0.0$.
3:     $\mathbf{state}\left(*\right)$ – Integer arrayCommunication 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.
4:     $\mathbf{x}\left({\mathbf{n}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: the $n$ pseudorandom numbers from the specified exponential distribution.
5:     $\mathbf{ifail}$ – IntegerInput/Output
On entry: ifail must be set to $0$, $-1\text{​ or ​}1$. If you are unfamiliar with this argument you should refer to Section 3.4 in How to Use the NAG Library and its Documentation for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value $-1\text{​ or ​}1$ is recommended. If the output of error messages is undesirable, then the value $1$ is recommended. Otherwise, if you are not familiar with this argument, the recommended value is $0$. When the value $-\mathbf{1}\text{​ or ​}\mathbf{1}$ 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, ${\mathbf{n}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{n}}\ge 0$.
${\mathbf{ifail}}=2$
On entry, ${\mathbf{a}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{a}}>0.0$.
${\mathbf{ifail}}=3$
On entry, state vector has been corrupted or not initialized.
${\mathbf{ifail}}=-99$
See Section 3.9 in How to Use the NAG Library and its Documentation for further information.
${\mathbf{ifail}}=-399$
Your licence key may have expired or may not have been installed correctly.
See Section 3.8 in How to Use the NAG Library and its Documentation for further information.
${\mathbf{ifail}}=-999$
Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.

Not applicable.

## 8Parallelism and Performance

g05sff 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 five pseudorandom numbers from an exponential distribution with mean $1.0$, generated by a single call to g05sff, after initialization by g05kff.

### 10.1Program Text

Program Text (g05sffe.f90)

### 10.2Program Data

Program Data (g05sffe.d)

### 10.3Program Results

Program Results (g05sffe.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017