-
Notifications
You must be signed in to change notification settings - Fork 41
/
circ_skewness.m
54 lines (48 loc) · 1.5 KB
/
circ_skewness.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
function [b, b0] = circ_skewness(alpha, w, dim)
%
% [b b0] = circ_skewness(alpha,w,dim)
% Calculates a measure of angular skewness.
%
% Input:
% alpha sample of angles
% [w weightings in case of binned angle data]
% [dim statistic computed along this dimension, default: 1st non-singular dimension]
%
% If dim argument is specified, all other optional arguments can be
% left empty: circ_skewness(alpha, [], dim)
%
% Output:
% b skewness (from Pewsey)
% b0 alternative skewness measure (from Fisher)
%
% References:
% Pewsey, Metrika, 2004
% Statistical analysis of circular data, Fisher, p. 34
%
% Circular Statistics Toolbox for Matlab
% By Philipp Berens, 2009
if nargin < 3
dim = find(size(alpha) > 1, 1, 'first');
if isempty(dim)
dim = 1;
end
end
if nargin < 2 || isempty(w)
% if no specific weighting has been specified
% assume no binning has taken place
w = ones(size(alpha));
else
if size(w,2) ~= size(alpha,2) || size(w,1) ~= size(alpha,1)
error('Input dimensions do not match');
end
end
% compute neccessary values
R = circ_r(alpha,w,[],dim);
theta = circ_mean(alpha,w,dim);
[~, rho2 mu2] = circ_moment(alpha,w,2,false,dim);
% compute skewness
theta2 = repmat(theta, size(alpha)./size(theta));
b = sum(w.*(sin(2*(circ_dist(alpha,theta2)))),dim)./sum(w,dim);
b0 = rho2.*sin(circ_dist(mu2,2*theta))./(1-R).^(3/2); % (formula 2.29)
end