NAG Library Routine Document

g05smf (dist_lognormal)


    1  Purpose
    7  Accuracy


g05smf generates a vector of pseudorandom numbers from a log-normal distribution with parameters μ and σ2.


Fortran Interface
Subroutine g05smf ( n, xmu, var, state, x, ifail)
Integer, Intent (In):: n
Integer, Intent (Inout):: state(*), ifail
Real (Kind=nag_wp), Intent (In):: xmu, var
Real (Kind=nag_wp), Intent (Out):: x(n)
C Header Interface
#include nagmk26.h
void  g05smf_ (const Integer *n, const double *xmu, const double *var, Integer state[], double x[], Integer *ifail)


The distribution has PDF (probability density function)
fx = 1 xσ2π exp - lnx-μ 2 2σ2 if ​ x>0 , fx=0 otherwise,  
i.e., lnx is normally distributed with mean μ and variance σ2. g05smf evaluates expyi, where the yi are generated by g05skf from a Normal distribution with mean μ and variance σ2, for i=1,2,,n.
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 g05smf.


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


1:     n – IntegerInput
On entry: n, the number of pseudorandom numbers to be generated.
Constraint: n0.
2:     xmu – Real (Kind=nag_wp)Input
On entry: μ, the mean of the distribution of lnx.
3:     var – Real (Kind=nag_wp)Input
On entry: σ2, the variance of the distribution of lnx.
Constraint: var0.0.
4:     state* – 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.
5:     xn – Real (Kind=nag_wp) arrayOutput
On exit: the n pseudorandom numbers from the specified log-normal distribution.
6:     ifail – IntegerInput/Output
On entry: ifail must be set to 0, -1​ 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​ 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 -1​ or ​1 is used it is essential to test the value of ifail on exit.
On exit: ifail=0 unless the routine detects an error or a warning has been flagged (see Section 6).

Error Indicators and Warnings

If on entry 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:
On entry, n=value.
Constraint: n0.
On entry, xmu is too large to take the exponential of xmu=value.
On entry, var=value.
Constraint: var0.0.
On entry, state vector has been corrupted or not initialized.
An unexpected error has been triggered by this routine. Please contact NAG.
See Section 3.9 in How to Use the NAG Library and its Documentation for further information.
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.
Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.


Not applicable.

Parallelism and Performance

g05smf 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.

Further Comments



This example prints five pseudorandom numbers from a log-normal distribution with mean 1.0 and variance 2.0, generated by a single call to g05smf, after initialization by g05kff.

Program Text

Program Text (g05smfe.f90)

Program Data

Program Data (g05smfe.d)

Program Results

Program Results (g05smfe.r)

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