I'm creating a plot but can't figure out how to remove the horizontal and vertical gridlines in this plot (marked by the red arrows).  Any suggestions?  Thanks. Here's my code & pic. /*Graphs and info of 2way Models*/ proc sgplot data=predpN_mm_bt; title "Predicted vs Actual Graph of 2way Model"; scatter x=pred_btpN_mm y=pN; lineparm x=0 y=0 slope=1 / legendlabel="1:1 line"; /** intercept, slope **/ yaxis grid values=(0.4 to 1.4 by 0.2) label="Measured pN (%)"; xaxis grid values=(0.4 to 1.4 by 0.2) label="Predicted pN Ground Reference (%)"; run;       ... View more

Hi, I'm running a PLS model with a "by" variable which has 2 levels (2014 vs. 2017). I've run CV to select the correct number of latent factors, but  for each of my "by" variables I need to use a different number of latent factors (3 vs. 5).  How do I tell it that if by=2014 use 3 factors and if by=2017 then use 5?  Here's the code for the cross-validation and the model with the factors. Thanks. /* Running Model By Year to separate out 2014 from 2017 */ /* Global Model with all bands at R1 */ proc pls data=splitplsr2 cv=random(seed=12345) cvtest varss plots=(diagnostics dmod scores ParmProfiles VIP XLoadingProfiles); by yr; model meas = R1Avg_412_d.......etc. R1Avg_917_d / solution; output OUT=test1; ods output VariableImportancePlot=vip; title 'Global PLS Full Model'; run; /* Model with Factors chosen */ proc pls data=splitplsr2 nfac=3 varss plots=(diagnostics dmod scores ParmProfiles VIP XLoadingProfiles); by year; model meas = R1Avg_412_d....etc. R1Avg_917_d / solution; output OUT=outfile predicted=predR1f press=pressR1f yresidual=yresidR1f ; ods output VariableImportancePlot=vip; title 'Global PLS Full Final Model'; run; ... View more

I'm working in SAS Enterprise Guide and have ODS GRAPHICS ON.  So I get a nice SAS Report in my results.   I would like to export Selected graphs at high dpi and still get all tables and graphs in the html output. How do I do that?     With current code shown below I'm only getting the selected  graph as separate files and that same limited output in the html report.  Thanks!   ods graphics on; options ls=78; /* ods trace on;*/ ODS LISTING GPATH = '\\User\SASOutput\' image_dpi=300; ODS GRAPHICS / RESET IMAGENAME = 'pN_CV_R1_' IMAGEFMT = TIFF; ODS SELECT CVPlot; ... View more

I'm new to running Proc PLS and I'm trying to understand if I still need to run cv after choosing the number of factors for my model. Here's an example of my code and what I'm doing.  Is that correct?  Thanks for your input. (note: I've purposely removed many of my x-vars from the model I'm showing below to save space) proc pls data=splitplsr2 cv=random(seed=12345) cvtest varss plots=(diagnostics dmod scores ParmProfiles VIP XLoadingProfiles); class plat; model pNmeas = plat R1Avg_412_d/ solution; output OUT=test1; ods output VariableImportancePlot=vip; title 'Global Model'; run; /* run model above and choose factors by van der Voet's test*/ /*next code to run for solutions using the designated number of factors*/ proc pls data=splitplsr2 nfac=8 varss plots=(diagnostics dmod scores ParmProfiles VIP XLoadingProfiles); class plat; model pNmeas = plat R1Avg_412_d/ solution; output OUT=outfile predicted=predpNR1f press=presspNR1f yresidual=yresidpNR1f ; ods output VariableImportancePlot=vip; title 'Final Global Model'; run; ... View more

I'm trying to split my data into Train (70%) and Test data sets.  My file has 508 rows, but the column I want to split only has about 350 cells filled.  The rest are empty.  I'm splitting the data through strata (3 cols) with simple random selection which seems to work, but it seems to be splitting the proportions from the 508 rows vs. the ~350 rows with actual data.  How do I get it to ignore the missing values in my data column "nce" for the split.  Here's my code. Thanks for the help. /*partitioning data into 2 sets at 70% split with stratification*/ /* new column Selected = 0 is the 30% Test set, Selected = 1 is the 70% Train set */ proc surveyselect data=phrs2cut method=srs samprate= 0.7 out=StratSRS seed=12345 outall; samplingunit nce; strata loc2 ntrt2 pd2 notsorted / alloc=proportional stats; title "After Split"; run; ... View more

I have one column (NC) that I want to copy to another new column (NCMeas), but whenever column "Selected" = 0 I want the new column "NCMeas" to be empty.  How do I do that?  These are all numeric columns. Thanks. data want; set have; NC = NCMeas; if Selected=0 then call NCMeas ????; run; ... View more

Hi.  I'm new to Proc PLS and noticed that when people talk of the results for their Proc PLS models they report Rsquare, RMSE and Standard error of the prediction (SEP).  With my code shown below I was able to get a plot of the Rsq for the model, but 1.  how do find that number for my final selected set of factors? 2.  how do I get it to show up on the measured-to-predicted plot?   3. how do i get the RMSE value outputted? 4. how do I calculate the SEP?  I was able to output my predicted values, but got lost there.   5.  how do I SAS to split my data into train (2/3 of data) and test (1/3)? proc pls data=WORK.PhRSData cv=split cvtest varss plots=(diagnostics dmod xyscores ParmProfiles VIP XLoadingProfiles); class loc hyb pd ntrt rep; model y = loc hyb pd ntrt rep(loc) var1 var2 var3 var4...var25 / solution; output OUT=outfile predicted=ypred press=press; ods output VariableImportancePlot=vip; title 'Global PLS NCE Model w/ All vars'; run; /* Reduced model with diagnostics -setting factors*/ proc pls data=WORK.PhRSData nfac=8 cv=split cvtest varss plots=(diagnostics dmod xyscores ParmProfiles VIP XLoadingProfiles); class loc hyb pd ntrt rep; model y = loc hyb pd ntrt rep(loc) var1 var2 var3 var4...var10 / solution; output OUT=outfile2 predicted=ypred2 press=press2; ods output VariableImportancePlot=vip2; title 'Reduced PLS Model with Bands & Vars'; run; ODS GRAPHICS OFF;   Thanks! ... View more

I've run a mixed model and want to plot the Actual by. Predicted values.  In JMP you can plot the predicted values or the Conditional predicted values (the values with Random Effects included) as the x-var.  I see that in Proc Mixed you have the option of saving the predicted values as OUTPRED=filename but is this using the Predicted or Conditional Predicted values?  Then, how do I graph them?  Thanks.   Or, is it better to use Proc PLM? proc mixed data=source; class hyb ntrt; model y = a b a*b / redidual outpred=predicted; random hyb ntrt hyb*ntrt ; lsmeans a b / pdiff=all cl adjust=tukey alpha=0.10; title 'Model A'; store ModA; run; proc plm restore=ModA; effectplot; run; ... View more