📄 anova.m
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## Copyright (C) 1995, 1996, 1997, 1998, 1999, 2000, 2002, 2005, 2006,## 2007 Kurt Hornik#### This file is part of Octave.#### Octave 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.#### Octave 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 Octave; see the file COPYING. If not, see## <http://www.gnu.org/licenses/>.## -*- texinfo -*-## @deftypefn {Function File} {[@var{pval}, @var{f}, @var{df_b}, @var{df_w}] =} anova (@var{y}, @var{g})## Perform a one-way analysis of variance (ANOVA). The goal is to test## whether the population means of data taken from @var{k} different## groups are all equal.#### Data may be given in a single vector @var{y} with groups specified by## a corresponding vector of group labels @var{g} (e.g., numbers from 1## to @var{k}). This is the general form which does not impose any## restriction on the number of data in each group or the group labels.#### If @var{y} is a matrix and @var{g} is omitted, each column of @var{y}## is treated as a group. This form is only appropriate for balanced## ANOVA in which the numbers of samples from each group are all equal.#### Under the null of constant means, the statistic @var{f} follows an F## distribution with @var{df_b} and @var{df_w} degrees of freedom.#### The p-value (1 minus the CDF of this distribution at @var{f}) is## returned in @var{pval}.#### If no output argument is given, the standard one-way ANOVA table is## printed.## @end deftypefn## Author: KH <Kurt.Hornik@wu-wien.ac.at>## Description: One-way analysis of variance (ANOVA)function [pval, f, df_b, df_w] = anova (y, g) if ((nargin < 1) || (nargin > 2)) print_usage (); elseif (nargin == 1) if (isvector (y)) error ("anova: for `anova (y)', y must not be a vector"); endif [group_count, k] = size (y); n = group_count * k; group_mean = mean (y); else if (! isvector (y)) error ("anova: for `anova (y, g)', y must be a vector"); endif n = length (y); if (! isvector (g) || (length (g) != n)) error ("anova: g must be a vector of the same length as y"); endif s = sort (g); i = find (s (2 : n) > s(1 : (n-1))); k = length (i) + 1; if (k == 1) error ("anova: there should be at least 2 groups"); else group_label = s ([1, (reshape (i, 1, k-1) + 1)]); endif for i = 1 : k; v = y (find (g == group_label (i))); group_count (i) = length (v); group_mean (i) = mean (v); endfor endif total_mean = mean (y(:)); SSB = sum (group_count .* (group_mean - total_mean) .^ 2); SST = sumsq (reshape (y, n, 1) - total_mean); SSW = SST - SSB; df_b = k - 1; df_w = n - k; v_b = SSB / df_b; v_w = SSW / df_w; f = v_b / v_w; pval = 1 - f_cdf (f, df_b, df_w); if (nargout == 0) ## This eventually needs to be done more cleanly ... printf ("\n"); printf ("One-way ANOVA Table:\n"); printf ("\n"); printf ("Source of Variation Sum of Squares df Empirical Var\n"); printf ("*********************************************************\n"); printf ("Between Groups %15.4f %4d %13.4f\n", SSB, df_b, v_b); printf ("Within Groups %15.4f %4d %13.4f\n", SSW, df_w, v_w); printf ("---------------------------------------------------------\n"); printf ("Total %15.4f %4d\n", SST, n - 1); printf ("\n"); printf ("Test Statistic f %15.4f\n", f); printf ("p-value %15.4f\n", pval); printf ("\n"); endifendfunction
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