www.gusucode.com > mbctools 工具箱 matlab 源码程序 > mbctools/@mdev_local/diagnosticStats.m
function [data,factors,standardPlotStr,olIndex]= diagnosticStats(mdev,SNo,X,Y,DataOK,m); % MDEV_LOCAL/DIAGNOSTICSTATS determine diagnostic stats for local node % % [data,factors,standardPlotStr,olIndex]= diagnosticStats(mdev,SNo,X,Y,DataOK); % Inputs % mdev modeldev object % SNo Test Number (default=1st fitted sweeps) % X,Y,DataOK Optional output from FitData(mdev,SNo); % Outputs % data diagnostic statistics in column-based matrix % factors names of signals in data matrix % standardPlotStr headings for special (lower) plots in model browser % olIndex index to potential outliers (note this index does not % include removed data) % Copyright 2000-2006 The MathWorks, Inc. and Ford Global Technologies, Inc. if nargin<2 SNo= find(mdev.FitOK,1,'first'); if isempty(SNo) SNo= 1; end end if nargin <6 m= LocalModel(mdev,SNo); end if nargin<5 || isempty(DataOK) % get data [X,Y,DataOK]= FitData(mdev,SNo); end Y(~DataOK)= NaN; %% get new diag stats for model [data,factors,standardPlotStr]= diagnosticStats(m,X,Y); % add monitor variables to scatter plot TP= mdevtestplan(mdev); mvars= getMonitor(TP); if ~isempty(mvars) & ~isempty(mvars.values) MDATA= getdata(TP,'ALLDATA'); MDATA= MDATA(:,mvars.values,SNo); MDATA= MDATA(DataOK,:); data = [data double(MDATA)]; factors= [factors(:); mvars.values(:)]'; end % outlier algorithm now uses monitor plot variables olIndex= outliers(m,data,factors); % add validation residual plots standardPlotStr= [standardPlotStr 'Validation residuals'];