%Segments and Missing data
%=========================
%
% Reference:
% S. de Waele,
% "Automatic model inference from finite time observations
% of stationary stochastic signals",
% Ph.D. Thesis, Delft university of Technology, 2003.
%
% This reference contains a comparison of different methods to
% deal with segments and missing data.
%
%
%Notation segments
% See DATA_SEGMENTS
%
%Notation missing data
% Measurements with missing data are denoted (ng,xg), where im contains
% the integer times at which the observations were done; xm contains
% the corresponding measurment values. Several segments of missing data
% can be combined into a cell.
% Example: to sets of data (ng1,xg1) and (ng2,xg2) can be combined as
% ng = {ng1 ng2};
% xg = {xg1 xg2};
%
%Conversions
% irr2grid - conversion of irregularly sampled data to missing data
% missing2seg - extraction of segments from missing data
%
%Estimation
% burg_s - (in ARMASA Toolbox) Burg type AR estimator for multiple segments
% burg_su - Burg type AR estimator for multiple segments of unequal length
% armasel_rs - (in ARMASA_RS dir) reduced statistics ARMAsel model identification
% sig2ar_misd - selection of AR models from measurements with missing data
% (uses ARShat_misd, ARhat_misd, ARMLfit).
