-
Notifications
You must be signed in to change notification settings - Fork 8
/
spm_Bcdf.m
91 lines (82 loc) · 3.01 KB
/
spm_Bcdf.m
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
function F = spm_Bcdf(x,v,w)
% Inverse Cumulative Distribution Function (CDF) of Beta distribution
% FORMAT F = spm_Bcdf(x,v,w)
%
% x - Beta variates (Beta has range [0,1])
% v - Shape parameter (v>0)
% w - Shape parameter (w>0)
% F - CDF of Beta distribution with shape parameters [v,w] at points x
%__________________________________________________________________________
%
% spm_Bcdf implements the Cumulative Distribution Function for Beta
% distributions.
%
% Definition:
%--------------------------------------------------------------------------
% The Beta distribution has two shape parameters, v and w, and is
% defined for v>0 & w>0 and for x in [0,1] (See Evans et al., Ch5).
% The Cumulative Distribution Function (CDF) F(x) is the probability
% that a realisation of a Beta random variable X has value less than
% x. F(x)=Pr{X<x}: This function is usually known as the incomplete Beta
% function. See Abramowitz & Stegun, 26.5; Press et al., Sec6.4 for
% definitions of the incomplete beta function.
%
% Variate relationships:
%--------------------------------------------------------------------------
% Many: See Evans et al., Ch5
%
% Algorithm:
%--------------------------------------------------------------------------
% Using MATLAB's implementation of the incomplete beta finction (betainc).
%
% References:
%--------------------------------------------------------------------------
% Evans M, Hastings N, Peacock B (1993)
% "Statistical Distributions"
% 2nd Ed. Wiley, New York
%
% Abramowitz M, Stegun IA, (1964)
% "Handbook of Mathematical Functions"
% US Government Printing Office
%
% Press WH, Teukolsky SA, Vetterling AT, Flannery BP (1992)
% "Numerical Recipes in C"
% Cambridge
%__________________________________________________________________________
% Copyright (C) 1999-2011 Wellcome Trust Centre for Neuroimaging
% Andrew Holmes
% $Id: spm_Bcdf.m 4182 2011-02-01 12:29:09Z guillaume $
%-Format arguments, note & check sizes
%--------------------------------------------------------------------------
if nargin<3, error('Insufficient arguments'), end
ad = [ndims(x);ndims(v);ndims(w)];
rd = max(ad);
as = [[size(x),ones(1,rd-ad(1))];...
[size(v),ones(1,rd-ad(2))];...
[size(w),ones(1,rd-ad(3))]];
rs = max(as);
xa = prod(as,2)>1;
if sum(xa)>1 && any(any(diff(as(xa,:)),1))
error('non-scalar args must match in size');
end
%-Computation
%--------------------------------------------------------------------------
%-Initialise result to zeros
F = zeros(rs);
%-Only defined for x in [0,1] & strictly positive v & w.
% Return NaN if undefined.
md = ( x>=0 & x<=1 & v>0 & w>0 );
if any(~md(:))
F(~md) = NaN;
warning('Returning NaN for out of range arguments');
end
%-Special cases: F=1 when x=1
F(md & x==1) = 1;
%-Non-zero where defined & x>0, avoid special cases
Q = find( md & x>0 & x<1 );
if isempty(Q), return, end
if xa(1), Qx=Q; else Qx=1; end
if xa(2), Qv=Q; else Qv=1; end
if xa(3), Qw=Q; else Qw=1; end
%-Compute
F(Q) = betainc(x(Qx),v(Qv),w(Qw));