-
Notifications
You must be signed in to change notification settings - Fork 1
/
spm_Pcdf.m
93 lines (86 loc) · 3.01 KB
/
spm_Pcdf.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
92
93
function F = spm_Pcdf(x,l)
% Cumulative Distribution Function (PDF) of Poisson distribution
% FORMAT F = spm_Ppdf(x,l)
%
% x - ordinates
% l - Poisson mean parameter (lambda l>0) [Defaults to 1]
% F - Poisson CDF
%_______________________________________________________________________
%
% spm_Pcdf implements the Cumulative Distribution Function of the
% Poisson distribution.
%
% Definition:
%-----------------------------------------------------------------------
% The Poisson Po(l) distribution is the distribution of the number of
% events in unit time for a stationary Poisson process with mean
% parameter lambda=1, or equivalently rate 1/l. If random variable X is
% the number of such events, then X~Po(l), and the CDF F(x) is
% Pr({X<=x}.
%
% F(x) is defined for strictly positive l, given by: (See Evans et al., Ch31)
%
% { 0 for x<0
% | _ floor(x)
% f(rx = | > l^i * exp(-l) / i!) for x>=0
% { - i=0
%
% Algorithm:
%-----------------------------------------------------------------------
% F(x), the CDF of the Poisson distribution, for X~Po(l), is related
% to the incomplete gamma function, by:
%
% F(x) = 1 - gammainc(l,x+1) (x>=0)
%
% See Press et al., Sec6.2 for further details.
%
% Normal approximation:
%-----------------------------------------------------------------------
% For large lambda the normal approximation Y~:~N(l,l) may be used.
% With continuity correction this gives
% F(x) ~=~ Phi((x+.5-l)/sqrt(l))
% where Phi is the standard normal CDF, and ~=~ means "appox. =".
%
% 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
%
%_______________________________________________________________________
% @(#)spm_Pcdf.m 2.2 Andrew Holmes 99/04/26
%-Format arguments, note & check sizes
%-----------------------------------------------------------------------
if nargin<2, l=1; end
if nargin<1, error('Insufficient arguments'), end
ad = [ndims(x);ndims(l)];
rd = max(ad);
as = [ [size(x),ones(1,rd-ad(1))];...
[size(l),ones(1,rd-ad(2))]; ];
rs = max(as);
xa = prod(as,2)>1;
if all(xa) & any(diff(as(xa,:)))
error('non-scalar args must match in size'), end
%-Computation
%-----------------------------------------------------------------------
%-Initialise result to zeros
F = zeros(rs);
%-Only defined for l>0. Return NaN if undefined.
md = ( ones(size(x)) & l>0 );
if any(~md(:)), F(~md) = NaN;
warning('Returning NaN for out of range arguments'), end
%-Non-zero only where defined and x>=0
Q = find( md & x>=0 );
if isempty(Q), return, end
if xa(1), Qx=Q; else Qx=1; end
if xa(2), Ql=Q; else Ql=1; end
%-Compute
F(Q) = 1 - gammainc(l(Ql),x(Qx)+1);