This file is indexed.

/usr/share/octave/packages/statistics-1.3.0/binostat.m is in octave-statistics 1.3.0-1.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
## Copyright (C) 2006, 2007 Arno Onken <asnelt@asnelt.org>
## Copyright (C) 2015 Carnë Draug <carandraug@octave.org>
##
## This program is free software; you can redistribute it and/or modify it under
## the terms of the GNU General Public License as published by the Free Software
## Foundation; either version 3 of the License, or (at your option) any later
## version.
##
## This program is distributed in the hope that it will be useful, but WITHOUT
## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
## details.
##
## You should have received a copy of the GNU General Public License along with
## this program; if not, see <http://www.gnu.org/licenses/>.

## -*- texinfo -*-
## @deftypefn {Function File} {[@var{m}, @var{v}] =} binostat (@var{n}, @var{p})
## Compute mean and variance of the binomial distribution.
##
## @subheading Arguments
##
## @itemize @bullet
## @item
## @var{n} is the first parameter of the binomial distribution. The elements
## of @var{n} must be natural numbers
##
## @item
## @var{p} is the second parameter of the binomial distribution. The
## elements of @var{p} must be probabilities
## @end itemize
## @var{n} and @var{p} must be of common size or one of them must be scalar
##
## @subheading Return values
##
## @itemize @bullet
## @item
## @var{m} is the mean of the binomial distribution
##
## @item
## @var{v} is the variance of the binomial distribution
## @end itemize
##
## @subheading Examples
##
## @example
## @group
## n = 1:6;
## p = 0:0.2:1;
## [m, v] = binostat (n, p)
## @end group
##
## @group
## [m, v] = binostat (n, 0.5)
## @end group
## @end example
##
## @subheading References
##
## @enumerate
## @item
## Wendy L. Martinez and Angel R. Martinez. @cite{Computational Statistics
## Handbook with MATLAB}. Appendix E, pages 547-557, Chapman & Hall/CRC,
## 2001.
##
## @item
## Athanasios Papoulis. @cite{Probability, Random Variables, and Stochastic
## Processes}. McGraw-Hill, New York, second edition, 1984.
## @end enumerate
## @end deftypefn

## Author: Arno Onken <asnelt@asnelt.org>
## Description: Moments of the binomial distribution

function [m, v] = binostat (n, p)

  if (nargin != 2)
    print_usage ();
  elseif (! isscalar (n) && ! isscalar (p) && ! size_equal (n, p))
    error ("binostat: N and P must be of common size or scalar");
  endif

  k = find (! (n > 0 & fix (n) == n & p >= 0 & p <= 1));

  # Calculate moments
  m = n .* p;
  m(k) = NaN;

  if (nargout > 1)
    v = m .* (1 - p);
    v(k) = NaN;
  endif

endfunction

%!test
%! n = 1:6;
%! p = 0:0.2:1;
%! [m, v] = binostat (n, p);
%! expected_m = [0.00, 0.40, 1.20, 2.40, 4.00, 6.00];
%! expected_v = [0.00, 0.32, 0.72, 0.96, 0.80, 0.00];
%! assert (m, expected_m, 0.001);
%! assert (v, expected_v, 0.001);

%!test
%! n = 1:6;
%! [m, v] = binostat (n, 0.5);
%! expected_m = [0.50, 1.00, 1.50, 2.00, 2.50, 3.00];
%! expected_v = [0.25, 0.50, 0.75, 1.00, 1.25, 1.50];
%! assert (m, expected_m, 0.001);
%! assert (v, expected_v, 0.001);

%!test
%! n = [-Inf -3 5 0.5 3 NaN 100, Inf];
%! [m, v] = binostat (n, 0.5);
%! assert (isnan (m), [true true false true false true false false])
%! assert (isnan (v), [true true false true false true false false])
%! assert (m(end), Inf);
%! assert (v(end), Inf);

%!assert (nthargout (1:2, @binostat, 5, []), {[], []})
%!assert (nthargout (1:2, @binostat, [], 5), {[], []})
%!assert (nthargout (1:2, @binostat, "", 5), {[], []})
%!assert (nthargout (1:2, @binostat, true, 5), {NaN, NaN})
%!assert (nthargout (1:2, @binostat, 5, true), {5, 0})

%!assert (size (binostat (randi (100, 10, 5, 4), rand (10, 5, 4))), [10 5 4])
%!assert (size (binostat (randi (100, 10, 5, 4), 7)), [10 5 4])