Provided by: libstatistics-test-randomwalk-perl_0.02-1_all

NAME

```       Statistics::Test::RandomWalk - Random Walk test for random numbers

```

SYNOPSIS

```         use Statistics::Test::RandomWalk;
my \$tester = Statistics::Test::RandomWalk->new();
\$tester->set_data( [map {rand()} 1..1000000] );

my \$no_bins = 10;
my (\$quant, \$got, \$expected) = \$tester->test(\$no_bins);
print \$tester->data_to_report(\$quant, \$got, \$expected);

```

DESCRIPTION

```       This module implements a Random Walk test of a random number generator as outlined in

Basically, it tests that the numbers "[0,1]" generated by a random number generator are
distributed evenly. It divides "[0,1]" into "n" evenly sized bins and calculates the
number of expected and actual random numbers in the bin. (In fact, this counts the
cumulated numbers, but that works the same.)

```

METHODS

```   new
Creates a new random number tester.

set_rescale_factor
The default range of the random numbers [0, 1) can be rescaled by a constant factor. This
method is the setter for that factor.

rescale_factor
Returns the current rescaling factor.

set_data
Sets the random numbers to operate on. First argument must be either an array reference to
an array of random numbers or a code reference.

If the first argument is a code reference, the second argument must be an integer "n". The
code reference is called "n"-times and its return values are used as random numbers.

The code reference semantics are particularly useful if you do not want to store all
random numbers in memory at the same time. You can write a subroutine that, for example,
generates and returns batches of 100 random numbers so no more than 101 of these numbers
will be in memory at the same time. Note that if you return 100 numbers at once and pass
in "n=50", you will have a sequence of 5000 random numbers.

test
Runs the Random Walk test on the data that was previously set using "set_data".

First argument must be the number of bins.

Returns three array references. First is an array of quantiles.  If the number of bins was
ten, this (and all other returned arrays) will hold ten items.

Second are the determined numbers of random numbers below the quantiles. Third are the
expected counts.

data_to_report
From the data returned by the "test()" method, this method creates a textual report and
returns it as a string.

Do not forget to pass in the data that was returned by "test()" or use the "test_report()"
method directly if you do not use the data otherwise.

```

SUBROUTINES

```   n_over_k
Computes "n" over "k". Uses Perl's big number support and returns a Math::BigFloat object.

This sub is memoized.

```

SEEALSO

```       Math::BigFloat, Memoize, Params::Util

Random number generators: Math::Random::MT, Math::Random, Math::Random::OO,
Math::TrulyRandom, "/dev/random" where available

Statistics::Test::Sequence

The algorithm was taken from: (German)

Blobel, V., and Lohrmann, E. Statistische und numerische Methoden der Datenanalyse.
Stuttgart, Leipzig: Teubner, 1998

```

AUTHOR

```       Steffen Mueller, <smueller@cpan.org>

```

```       Copyright (C) 2007-2010 by Steffen Mueller