www.gusucode.com > mbcmodels 工具箱 matlab 源码程序 > mbcmodels/@localmod/localsummary.m
function [labs,head,Stats,InSig]= localsummary(L,Type,TS,X,Y,Wc,ValRMSE) %LOCALSUMMARY summary statistics in local diagnostics table % % % [labs,Stats]= localsummary(L,Xs,Ys,Wc,ls) % Copyright 2006-2015 The MathWorks, Inc. and Ford Global Technologies, Inc. TypeList= { 'Summary Statistics',... 'Parameters',... 'Correlations',... 'Response Features',... 'Global Covariance'}; if nargin==1 labs= TypeList; head= ''; Stats=[]; InSig = []; else [Xs,~]= checkdata(L,X{1},Y); params= double(L); switch Type case 1 % diagnostics [Stats,labs]= FitSummary(L,X{1},Y,Wc); InSig= false(size(Stats)); head=''; labs= [labs 'Validation RMSE']'; Stats= [Stats ValRMSE]'; case 2 % parameters labs= labels(L,0); head= {'Value','Std Error'}; if isempty(params) Stats= zeros(0,2); InSig= false(0,0); else [~,W]= sigma(L,Xs{1},Wc); Stats= [double(L) sqrt(diag(W))]; InSig= abs(Stats(:,1))<tinv(0.99,dferror(L))*Stats(:,2); end case 3 % correlation matrix labs= labels(L,0); head = labs; if isempty(params) labs= {''}; head={''}; Stats= NaN; else [~,W]= sigma(L,Xs{1},Wc); [~,Stats]= xregcov2corr(W); end InSig= false(size(Stats,1),1); case 4 % 'rf' labs= RespFeatName(L); % labs= detex(labs); head= {'Value','Std Error'}; Vals= evalfeatures(L); if ~isempty(Vals) S= sigma(L,Xs{1},Wc); Stats= [Vals(:) sqrt(diag(S))]; InSig= abs(Stats(:,1))<tinv(0.99,dferror(L))*Stats(:,2); else Stats= zeros(0,2); InSig= Stats; end case 5 % global covariance if numfeats(L)>0 labs= RespFeatName(L); head= labs'; if ~isempty(TS); Stats= cov(TS); if isempty(Stats) Stats= zeros(length(labs)); Stats(:)=NaN; end else Stats= zeros(length(labs)); Stats(:)=NaN; end InSig= false(size(Stats,1),1); else labs=cell(1,0); head= labs'; Stats= zeros(0,0); InSig= Stats; end end end