I am using the von Bertalanffy growth function (VBGF), but the PROC STATEMENT does not provide model fitness parameters such as AIC, BIC, RMSE, and R2? Need help to revise the PROC STATEMENT. FILENAME REFFILE '/home/u58890255/Growth functions/sample_data.xlsx'; PROC IMPORT DATAFILE=REFFILE DBMS=XLSX OUT=WORK.IMPORT; GETNAMES=YES; RUN; PROC CONTENTS DATA=WORK.IMPORT; RUN; title 'von Bertalanffy growth function'; data exp; set WORK.IMPORT; if expno=1; run; proc nlin data=exp method=marquardt; parms Linf=190 k=0.05 t0=-1.5; model sl=Linf*(1-exp(-k*(age-t0))); output out=expp p=pLinf r=Linf_residual; run; Using the following PROC STATEMENT,  I can calculate the adjusted R2 for a Nonlinear regression model, but this time the following PROC also does not provide any result proc summary data=expp; var Linf_residual Linf; output out=stats css(Linf)=sstot uss(Linf_residual)=ssres N=N; run; data expp; set stats; rsquared=1-(ssres/sstot); adjrsquared = 1-(1-rsquared)*(N-1) / (N- 3 -1); run; proc print data=expp; run; Kind regards, ... View more

Hello, I am trying to estimate six different parameters from my data using the following PROC, but the 95% CI of one parameter is too large (Parameter T). When I fixed “parameter A” with its estimated value in the second round, the 95% CI of “parameter T” also gets reduced. How can I fix this issue without fixing “parameter A”? Output SAS results are provided as a PDF attachment. Many thanks for the help   proc nlin data=exp method=marquardt; parms RLTE=0.00132 B=0.5 C=0.8 A=0.08 T=3 TU=20; R=RLTE*predlcm**C*EXP(A*temp)*(1-EXP(T*(temp-TU))); s=sow**(1-B)-R*(1-B)*time; if s>0 then stx=s**(1/(1-B)); else stx=0; model stw=stx; output out=expp p=pstw r=stw_residual; run; proc summary data=expp; var stw_residual stw; output out=stats css(stw)=sstot uss(stw_residual)=ssres N=N; run; data expp; set stats; rsquared=1-(ssres/sstot); adjrsquared = 1-(1-rsquared)*(N-1) / (N- 4 -1); run; proc print data=expp; run; ... View more