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hmminit.m
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hmminit.m
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function Q = hmminit(X, f, varargin)
% Q = hmminit(X, f, sord);
%
% Generate initial values for the controlling parameters Q (mean and
% variance) of a 2-state HMM; the outlier population uses the outermost f%
% of X values.
%
% INPUTS
% X Preprocessed data in column vectors
% f0 Initial outlier fraction
% sord Sort order
%
% OUTPUTS
% t Parameters theta for test distributions, with row ordering:
% 1 m1 Mean of outlier population
% 2 m0 Mean of null population
% 3 v1 Variance of outlier population
% 4 v0 Variance of null population
%
% ========================================================================
% Author: Joshua Jones, [email protected]
% Version: 1.0, 2016-02-29
s = {'abs'; 'descend'};
if numel(varargin) > 0
if ~isempty(varargin{1})
s = varargin{1};
end
end
if numel(s) == 1
s{2} = 'descend';
end
Nx = size(X,1);
F0 = round(f*Nx);
% Generate trial values using a sorted X
switch lower(s{1})
case 'abs'
X0 = sort(abs(X),1,s{2});
case 'sq'
X0 = sort(X.^2,1,s{2});
otherwise
X0 = sort(X,1,s{2});
end
Q = [mean(X0(1:F0,:)); mean(X0(F0+1:end,:)); ...
var(X0(1:F0,:)); var(X0(F0+1:end,:))];