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Structural_Break.m
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Structural_Break.m
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function [nbr, datese, mBIC, lBIC] = structural_break(modelProbs, CI_lv, doBIC)
% This function is a simple procedure to automize getting output from the
% univariate structural break model by J. Bai and P. Perron, as implemented
% by Yohei Yamamoto. It requires the m_break toolbox.
% link
% -----------------------------------------------------------------------------------------
% Inputs:
% modelProbs = row vector of data (in our case AMICA model probabilities or
% probability weights for every trial)
% CI_lv = confidence level at which to run Sequential Procedure
% 1 = 10%
% 2 = 5%
% 3 = 2.5%
% 4 = 1%
% -----------------------------------------------------------------------------------------
% Outputs:
% nbr = Number of breaks estimated by Sequential Procedure
% datese = Location of break estimated by Sequential Procedure
% mBIC = Number of breaks estimated by BIC
% lBIC = Location of breaks estimated by BIC (Global Optimization Procedure)
% -----------------------------------------------------------------------------------------
% Written by Sven Wientjes at the UvA
% Master Brain & Cognitive Sciences research intern at the Van Maanen lab for Mathematical Psychology and
% Cognitive Modeling (MPCM)
%% Start Structural Break procedure
% Add the m_break folder to the path
addpath('E:\m_break')
yyy = modelProbs';
bigt=length(yyy);
y=yyy;
z=ones(bigt,1);
x=[];
q=1; % number of regressors z
p=0; % number of regressors x
m=5; % maximum number of structural changes allowed
eps1=.15; % value of the trimming (in percentage) for the construction
% and critical values of the supF type tests (used in the
% supF test, the Dmax, the supF(l+1|l) and the sequential
% procedure). If these tests are used, h below should be set
% at int(eps1*bigt). But if the tests are not required,
% estimation can be done with an arbitrary h. There are five
% options: eps1= .05, .10, .15, .20, or .25. For each option,
% the maximal value of m above is: 10 for eps=.05, 8 for
% eps1=.10, 5 for eps1=.15, 3 for eps1=.20, and 2 for eps1=.25.
h=round(eps1*bigt); % minimal length of a segment (h >= q). Note: if robust=1, h
% should be set at a larger value.
% The followings are options if p > 0 -------------------------------
fixb=0; % set to 1 if use fixed initial values for beta
betaini=0; % if fixb=1, load the initial value of beta
maxi=20; % maximum number of iterations for the nonlinear procedure to
% obtain global minimizers
printd=1; % set to 1 if want the output from the iterations to be printed
eps=0.0001; % criterion for the convergence
% --------------------------------------------------------------------
robust=1; % set to 1 if want to allow for heterogeneity and autocorrelation
% in the residuals, 0 otherwise. The method used is Andrews(1991)
% automatic bandwidth with AR(1) approximation and the quadratic
% kernel. Note: Do not set to 1 if lagged dependent variables are
% included as regressors.
prewhit=1; % set to 1 if want to apply AR(1) prewhitening prior to estimating
% the long run covariance matrix.
hetdat=1; % option for the construction of the F tests. Set to 1 if want to
% allow different moment matrices of the regressors across segments.
% If hetdat=0, the same moment matrices are assumed for each segment
% and estimated from the ful sample. It is recommended to set
% hetdat=1 if p>0.
hetvar=1; % option for the construction of the F tests.Set to 1 if want to allow
% for the variance of the residuals to be different across segments.
% If hetvar=0, the variance of the residuals is assumed constant
% across segments and constructed from the ful sample. This option
% is not available when robust=1.
hetomega=1; % used in the construction of the confidence intervals for the break
% dates. If hetomega=0, the long run covariance matrix of zu is
% assumed identical across segments (the variance of the errors u
% if robust=0)
hetq=1; % used in the construction of the confidence intervals for the break
% dates. If hetq=0, the moment matrix of the data is assumed identical
% across segments.
doglobal=1; % set to 1 if want to cal the procedure to obtain global minimizers
dotest=1; % set to 1 if want to construct the supF, UDmax and WDmax tests
% doglobal must be set to 1 to run this procedure.
dospflp1=1; % set to 1 if want to construct the supF(l+1|l) tests where under
% the null the l breaks are obtained using global minimizers.
% doglobal must be set to 1 to run this procedure.
doorder=1; % set to 1 if want to cal the procedure that selects the number of
% breaks using information criteria. doglobal must be set to 1 to
% run this procedure.
dosequa=1; % set to 1 if want to estimate the breaks sequentialy and estimate
% the number of breaks using supF(l+1|l) test
dorepart=1; % set to 1 if want to modify the break dates obtained from the
% sequential method using the repartition method of Bai (1995),
% Estimating breaks one at a time. This is needed for the confidence
% intervals obtained with estim below to be valid.
estimbic=1; % set to 1 if want to estimate the model with the number of breaks
% selected by BIC.
estimlwz=0; % set to 1 if want to estimate the model with the number of breaks
% selected by LWZ
estimseq=1; % set to 1 if want to estimate the model with the number of breaks
% selected using the sequential procedure
estimrep=0; % set to 1 if want to estimate the model with the breaks selected
% using the repartition method
estimfix=0; % set to 1 if want to estimate the model with a prespecified number
% of breaks equal to fixn set below
fixn=0;
% Get sequential procedure nBreaks & Locations
[nbr, datese]=sequa(m,CI_lv,q,h,bigt,robust,prewhit,z,y,x,p,hetdat,hetvar,eps1);
if isempty(datese)
datese = 0;
end
if doBIC == 1
% Estimate models (for application of information criteria: BIC)
if p==0 %Partial check
[glob,datevec,bigvec]=dating(y,z,h,m,q,bigt);
else
disp('This is a partial structural change model and the following')
disp('specifications were used:')
disp(['The number of regressors with fixed coefficients, p: ' num2str(p)])
disp(['Whether (1) or not (0) the initial values of beta are fixed: ' num2str(fixb)])
disp(['If so, at the following values: ' num2str(betaini)])
disp(['The convergence criterion is: ' num2str(eps)])
disp(['Whether (1) or not (0) the iterations are printed: ' num2str(printd)])
disp('----------------------')
[glob,datevec,bigvec]=nldat(y,z,x,h,m,p,q,bigt,fixb,eps,maxi,betaini,printd);
end
if p==0
zz=z; %Partial check
else
zz=[z x];
end
ssrzero=ssrnul(y,zz); %Idk check
% Get BIC nBreaks
[mBIC, whatever] = order(ssrzero,glob,bigt,m,q); %Where do ssrzero and globl come from?
% Get BIC Locations
if mBIC ~= 0
lBIC = datevec(1:mBIC,mBIC);
else
lBIC= 0;
end
else
mBIC = 'Not Applicable';
lBIC = 'Not Applicable';
end
end