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Stepwisefit changing yy variable...

1 次查看（过去 30 天）
Robert
Robert 2016-1-21
关闭： MATLAB Answer Bot 2021-8-20
I have written a code for a stepwise regression. Usually there would be one yy variable and multiple xx variables. Part of the difference between my xx variables is a certain lag (0-6).
The problem is that where a lag exists in an xx variable, it must be matched in the yy variable, so the yy variable needs to change according to the xx variable and vice versa. See the code below (Not including loading data). Thank you in advance for any help
for j = 1:1505
Nc0=NDVI(1:end,j);
A1c0=Approx1 (1:end-0,j);
A2c0=Approx2 (1:end-0,j);
A3c0=Approx3 (1:end-0,j);
A4c0=Approx4 (1:end-0,j);
D1c0=Det1 (1:end-0,j);
D2c0=Det2 (1:end-0,j);
D3c0=Det3 (1:end-0,j);
D4c0=Det4 (1:end-0,j);
Nc1=NDVI(1+1:end,j);
A1c1=Approx1 (1:end-1,j);
A2c1=Approx2 (1:end-1,j);
A3c1=Approx3 (1:end-1,j);
A4c1=Approx4 (1:end-1,j);
D1c1=Det1 (1:end-1,j);
D2c1=Det2 (1:end-1,j);
D3c1=Det3 (1:end-1,j);
D4c1=Det4 (1:end-1,j);
Nc2=NDVI(1+2:end,j);
A1c2=Approx1 (1:end-2,j);
A2c2=Approx2 (1:end-2,j);
A3c2=Approx3 (1:end-2,j);
A4c2=Approx4 (1:end-2,j);
D1c2=Det1 (1:end-2,j);
D2c2=Det2 (1:end-2,j);
D3c2=Det3 (1:end-2,j);
D4c2=Det4 (1:end-2,j);
Nc3=NDVI(1+3:end,j);
A1c3=Approx1 (1:end-3,j);
A2c3=Approx2 (1:end-3,j);
A3c3=Approx3 (1:end-3,j);
A4c3=Approx4 (1:end-3,j);
D1c3=Det1 (1:end-3,j);
D2c3=Det2 (1:end-3,j);
D3c3=Det3 (1:end-3,j);
D4c3=Det4 (1:end-3,j);
Nc4=NDVI(1+4:end,j);
A1c4=Approx1 (1:end-4,j);
A2c4=Approx2 (1:end-4,j);
A3c4=Approx3 (1:end-4,j);
A4c4=Approx4 (1:end-4,j);
D1c4=Det1 (1:end-4,j);
D2c4=Det2 (1:end-4,j);
D3c4=Det3 (1:end-4,j);
D4c4=Det4 (1:end-4,j);
Nc5=NDVI(1+5:end,j);
A1c5=Approx1 (1:end-5,j);
A2c5=Approx2 (1:end-5,j);
A3c5=Approx3 (1:end-5,j);
A4c5=Approx4 (1:end-5,j);
D1c5=Det1 (1:end-5,j);
D2c5=Det2 (1:end-5,j);
D3c5=Det3 (1:end-5,j);
D4c5=Det4 (1:end-5,j);
Nc6=NDVI(1+0:end,j);
A1c6=Approx1 (1:end-6,j);
A2c6=Approx2 (1:end-6,j);
A3c6=Approx3 (1:end-6,j);
A4c6=Approx4 (1:end-6,j);
D1c6=Det1 (1:end-6,j);
D2c6=Det2 (1:end-6,j);
D3c6=Det3 (1:end-6,j);
D4c6=Det4 (1:end-6,j);
yy = Nc0; %THIS IS WHERE THE PROBLEM OCCURS, I NEED yy TO INCLUDE Nc0, Nc1, Nc2 ETC BUT ONLY TO %WORK WITH THE CORRESPONDING xx
xx=[A1c0, A2c0, A3c0, A4c0, D1c0, D2c0, D3c0, D4c0,A1c1, A2c1, A3c1, A4c1, D1c1, D2c1, D3c1, D4c1,...
A1c2, A2c2, A3c2, A4c2, D1c2, D2c2, D3c2, D4c2,A1c3, A2c3, A3c3, A4c3, D1c3, D2c3, D3c3, D4c3,...
A1c4, A2c4, A3c4, A4c4, D1c4, D2c4, D3c4, D4c4,A1c5, A2c5, A3c5, A4c5, D1c5, D2c5, D3c5, D4c5,...
A1c6, A2c6, A3c6, A4c6, D1c6, D2c6, D3c6, D4c6];
%Begin Stepwise Regression
if isnan(Nc0)
continue
else
[B,SE,PVAL,INMODEL,STATS,NEXTSTEP,HISTORY]= ...
stepwisefit(xx,yy,'penter',.05);
A1nolag(j)=INMODEL(1);
A2nolag(j)=INMODEL(2);
A3nolag(j)=INMODEL(3);
A4nolag(j)=INMODEL(4);
D1nolag(j)=INMODEL(5);
D2nolag(j)=INMODEL(6);
D3nolag(j)=INMODEL(7);
D4nolag(j)=INMODEL(8);
A11lag(j)=INMODEL(9);
A21lag(j)=INMODEL(10);
A31lag(j)=INMODEL(11);
A41lag(j)=INMODEL(12);
D11lag(j)=INMODEL(13);
D21lag(j)=INMODEL(14);
D31lag(j)=INMODEL(15);
D41lag(j)=INMODEL(16);
A12lag(j)=INMODEL(17);
A22lag(j)=INMODEL(18);
A32lag(j)=INMODEL(19);
A42lag(j)=INMODEL(20);
D12lag(j)=INMODEL(21);
D22lag(j)=INMODEL(22);
D32lag(j)=INMODEL(23);
D42lag(j)=INMODEL(24);
A13lag(j)=INMODEL(25);
A23lag(j)=INMODEL(26);
A33lag(j)=INMODEL(27);
A43lag(j)=INMODEL(28);
D13lag(j)=INMODEL(29);
D23lag(j)=INMODEL(30);
D33lag(j)=INMODEL(31);
D43lag(j)=INMODEL(32);
A14lag(j)=INMODEL(33);
A24lag(j)=INMODEL(34);
A34lag(j)=INMODEL(35);
A44lag(j)=INMODEL(36);
D14lag(j)=INMODEL(37);
D24lag(j)=INMODEL(38);
D34lag(j)=INMODEL(39);
D44lag(j)=INMODEL(40);
A15lag(j)=INMODEL(41);
A25lag(j)=INMODEL(42);
A35lag(j)=INMODEL(43);
A45lag(j)=INMODEL(44);
D15lag(j)=INMODEL(45);
D25lag(j)=INMODEL(46);
D35lag(j)=INMODEL(47);
D45lag(j)=INMODEL(48);
A16lag(j)=INMODEL(49);
A26lag(j)=INMODEL(50);
A36lag(j)=INMODEL(51);
A46lag(j)=INMODEL(52);
D16lag(j)=INMODEL(53);
D26lag(j)=INMODEL(54);
D36lag(j)=INMODEL(55);
D46lag(j)=INMODEL(56);
sstotApprox1(j)=STATS.SStotal; %calculate R^2
ssresidApprox1(j)=STATS.SSresid;
rsq = 1- ssresidApprox1./sstotApprox1;
rsq(rsq==Inf) = NaN ; %Set Inf to NaN
rmse(j)=STATS.rmse; %Extract rmse
rmse(rmse==Inf) = NaN; %Set Inf to NaN
% repeat regresson only on the sigificant variables
if sum(INMODEL,2)>0
xxn = zeros(size(xx,1),8);
xip=0;
for k=1:8 %8 refers to previous 8 variables including intecept
if INMODEL(1,k)==1
xip=xip+1;
xxn(:,xip)=xx(:,k); %these should now be the correct dimension
end
end
[Bn,SEn,PVALn,INMODELn,STATSn,NEXTSTEPn,HISTORYn]= ...
stepwisefit(xxn,yy,'penter',.05);
rmsen(j)=STATSn.rmse; %Extract rmse
rmsen = [rmse,zeros];
rmsen(rmse==0) = NaN; %Set Inf to NaN
sstotApprox1(j)=STATSn.SStotal; %calculate R^2
ssresidApprox1(j)=STATSn.SSresid;
rsqn = 1- ssresidApprox1./sstotApprox1
rsqn = [rsqn,zeros];
rsqn(rsq==0) = NaN
yest=xxn*Bn+STATSn.intercept
R1 = sum((yy-mean(yy)).*(yest-mean(yest)))
R2 = (sum((yy-mean(yy)).^2)).^.5
R3 = (sum((yest-mean(yest)).^2)).^.5
R = (R1/((R2)*(R3)))
testR(1,j)=R;
end
end
end

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