Hi Ingrid,   Sorry I hadn't seen your post. If mccv outputs it then yes it would be easy to add it. I'll look into it.   Thanks for your interest, Yves ... View more

Hi Raewdy,   Here is the script for it. Regards, Yves Names Default To Here( 1 ); Clear Globals(); // // Check host and R connection // macsys = Host is( "Mac" ); winsys = Host is( "Windows" ); connected = R Is Connected(); R Term(); If( connected == 0, If( macsys == 1, Set Environment Variable( "R_HOME", "/Library/Frameworks/R.framework/Versions/Current/Resources" ) ); If( winsys == 1, ppath = Pick Directory( "Locate the directory of your R program version 3.3.3" ); ppath=substr(ppath,2,length(ppath)-1); part = Parse( Eval Insert( " Set Environment Variable( \!"R_HOME\!",\!"^ppath^\!" );" ) ); Eval( part ); ); ); R Init(); connected = R Is Connected(); R Term(); If( connected == 0, ww2 = New Window( "Warning", Spacer Box(), Text Box( " CANNOT ESTABLISH CONNECTION WITH R " ), Spacer Box(), H Center Box( Button Box( "OK", ww2 << close window; ) ) ); Stop(); ); // // CHECK R VERSION // R Init(); connected = R Is Connected(); If( connected == 1, Rver = Char( R Get Version() ); If( Rver == "[3 3 3]", , ww1 = New Window( "Warning", <<Modal, Spacer Box(), Text Box( " THIS ADD-IN REQUIRES R version 3.3.3 " ), Spacer Box(), H Center Box( Button Box( "OK", ww1 << close window ) ) ); Set Environment Variable( "R_HOME", "C:/Program Files/R/R-3.3.3/" ); Stop(); ); ); dt = Current Data Table(); If( Is Empty( dt ), Try( dt = Open(), Throw( "No data table found" ) ) ); allvars = dt << get column names( string ); families = ({"gaussian", "binomial", "Gamma", "poisson"}); meths = ({"REML", "GCV Cp", "GACV Cp", "ML"}); aa = Associative Array( {1, 2, 3, 4}, {"REML", "GCV.Cp", "GACV.Cp", "ML"} ); aa2 = Associative Array( {1, 2, 3, 4}, {"gaussian", "binomial", "Gamma", "poisson"} ); aa3 = Associative Array( {"gaussian", "binomial", "Gamma", "poisson"}, {lnkgauss, lnkbinomial, lnkgamma, lnkpoisson} ); gamma = 1; lnkgauss = ({"identity", "log", "inverse"}); lnkbinomial = ({"logit", "probit", "cauchit", "log", "cloglog"}); lnkgamma = ({"identity", "log", "inverse"}); lnkpoisson = ({"identity", "log", "sqrt"}); tt = lnkgauss; sellnk = "identity"; selfam = "gaussian"; pog = 0; cw = 0; nw = New Window( "GAM Modelling", H List Box( V List Box( Panel Box( "Select Columns", MDSColList = Col List Box( All, width( 140 ), nlines( 10 ) ) ), H List Box( Outline Box( "Family", rb1 = Combo Box( families, selfam = rb1 << getselected(); tt = aa3 << getvalue( selfam ); cb << set items( tt ); ) ), ob = Outline Box( "Link", cb = Combo Box( tt, sellnk = cb << Getselected(); ) ) ), H List Box( Outline Box( "Method", rb2 = Radio Box( meths ) ), Outline Box( "Smoothness", H List Box( tb = Text Box( "Gamma: " ), sb = Number Edit Box( gamma, 3 ) ), ) ), ) , V List Box( Panel Box( "Cast Selected Columns into Roles", Lineup Box( N Col( 2 ), Spacing( 3 ), Button Box( "Y", GAM_YVar << Append( MDSColList << GetSelected ) ), GAM_YVar = Col List Box( width( 140 ), nLines( 1 ), MinItems( 1 ) ), Mbb = Button Box( "Linear X variables", GAM_L_XVar << Append( MDSColList << GetSelected ) ), //for SAS - matrix var to specify diff subjects; GAM_L_XVar = Col List Box( width( 140 ), nLines( 5 ) ), Button Box( "Smoothed X variables", GAM_S_XVar << Append( MDSColList << GetSelected ) ), GAM_S_XVar = Col List Box( width( 140 ), nLines( 5 ), MinItems( 1 ) ), Button Box( "Remove", GAM_YVar << RemoveSelected; GAM_L_XVar << RemoveSelected; GAM_S_XVar << RemoveSelected; ), ), ), tb5 = Text Box( "Options:" ), cbp = Check Box( {"Show data points in smoother plots"}, pog = cbp << Get() ), kdo = Check Box( {"Keep dialog open"} ), kdo << set( 1, 1 ); cw = kdo << Get(); , // ), //end HListBox Text Box( " " ), H List Box( Button Box( "Run", Yvar = GAM_YVar << Get Items; // S_X_vars = GAM_S_XVar << Get Items; L_X_vars = GAM_L_XVar << Get Items; fam = rb1 << Get; method = rb2 << Get; npterms = N Items( L_X_vars ) + 1; Nxvar = N Items( S_X_vars ); gamma = sb << get; If( pog == 1, Rpog = "TRUE", Rpog = "FALSE" ); // // Main portion // xvars = S_X_vars; xcode = ""; R Init(); pterms = List( "intercept" ); TYV = Dt << Get as matrix( Column( Yvar ) ); // LY = Min( YV ) * .95; // HY = Max( YV ) * 1.05; ndt = N Row( dt ); SV = ""; LV= ""; R Send( dt ); R Submit( "Rnames<-names(dt)" ); RnamesinJMP = R Get( Rnames ); aan = Associative Array( Allvars, RnamesinJMP ); sterms = List( "" ); RYvar = aan << Get value( Yvar[1] ); For( i = 1, i < npterms, i++, LXvar = aan << Get value( L_X_vars[i] ); Insert Into( pterms, Char( L_X_vars[i] ) ); xcode ||= Eval Insert( "^LXvar^+" ); ); For( i = 1, i <= Nxvar, i++, RXvar = aan << Get value( xvars[i] ); Insert Into( sterms, Char( xvars[i] ) ); xcode ||= Eval Insert( "s(^RXvar^)+" ); ); TSV = dt << Get as matrix( S_X_vars ); TLV = dt << Get as matrix( L_X_vars ); TAV = TYV; If( npterms > 1, TAV ||= TLV ); If( Nxvar >= 1, TAV ||= TSV, Print( "Please select variables" ) ); nm = Loc Nonmissing( TAV ); nnm=n row(nm); SV=TSV[nm]; LV=TLV[nm]; YV=TYV[nm]; LY = Min( YV ) * .95; HY = Max( YV ) * 1.05; if(nnm<npterms+Nxvar, ww3 = New Window( "Warning", Spacer Box(), Text Box( " FEWER OBSERVATIONS THAN PARAMETERS " ), Spacer Box(), H Center Box( Button Box( "OK", ww3 << close window; ) ) ); stop(); ); sterms = sterms[2 :: nxvar + 1]; xcode = Substr( xcode, 1, Length( xcode ) - 1 ); Rcode = "library(mgcv)"; Rcode ||= Eval Insert( "\[ b <- gam(^RYvar^~^xcode^,data=dt,method="^aa<<getvalue(method)^", family="^aa2<<getvalue(fam)^(link=^sellnk^)",gamma=^gamma^) sumb<-summary(b) fv<-b$fitted.values rsq<-as.list(sumb$r.sq) dev<-as.list(sumb$dev.expl) ptable<-as.list(sumb$p.table) spcrit<-as.list(sumb$sp.criterion) stable<-as.list(sumb$s.table) nobs<-as.list(sumb$n) parest<-as.list(sumb$p.coeff) pt<-(sumb$p.t) plot.gam(b,pages=1,residuals=^Rpog^,cex=2,all.terms=TRUE,pers=TRUE, shade=TRUE, pch=20) ]\" ); R Init(); R Submit( Rcode ); SmPl = R Get Graphics( "png" ); ptable = R Get( ptable ); stable = R Get( stable ); spcrit = R Get( spcrit ); rsq = R Get( rsq ); dev = R Get( dev ); nobs = R Get( nobs ); fitvalues = J( N Row( TYV ), 1, . ); tfv = R Get( fv ); fitvalues = tfv; LYH = Min( fitvalues ) * .95; HYH = Max( fitvalues ) * 1.05; Resids = TYV[nm] - transpose(fitvalues); LR = Min( Resids ) * 1.05; HR = Max( Resids ) * 1.05; If( Abs( LR ) >= HR, HR = Abs( LR ), LR = -HR ); R Term(); genfit = rsq || dev || nobs; pest = J( npterms, 1, . ); pstderr = J( npterms, 1, . ); pt = J( npterms, 1, . ); pprob = J( npterms, 1, . ); For( i = 1, i <= npterms, i++, pest[i] = ptable[i]; pstderr[i] = ptable[i + 1 * npterms]; pt[i] = ptable[i + 2 * npterms]; pprob[i] = If( ptable[i + 3 * npterms] <= 0.0001, 0.0001, ptable[i + 3 * npterms] ); ); sedf = J( nxvar, 1, . ); srdf = J( nxvar, 1, . ); sf = J( nxvar, 1, . ); sprob = J( nxvar, 1, . ); For( i = 1, i <= nxvar, i++, sedf[i] = stable[i]; srdf[i] = stable[i + nxvar * 1]; sf[i] = stable[i + 2 * nxvar]; sprob[i] = If( stable[i + 3 * nxvar] <= 0.0001, 0.0001, stable[i + 3 * nxvar] ); ); New Window( "GAM Model Fit", Outline Box( Eval Insert( "Family: ^selfam^" ) ), Outline Box( Eval Insert( "Link function: ^sellnk^" ) ), Outline Box( "Whole Model", {"Save predicted", New Column( "Predicted values", values( fitvalues ) ), "Save residuals", New Column( "Residuals", values( YV - fitvalues ) )}, H List Box( V List Box( Outline Box( "Obs vs Pred.", Graph Box( X Scale( LYH, HYH ), Y Scale( LY, HY ), Yname( "Obs Y" ), Xname( "Pred Y" ), Frame Size( 250, 250 ), Line( {LY, LY}, {HY, HY} ), Marker( Marker State( 0 ), fitvalues, YV ) ) ), Outline Box( "Residuals vs Pred.", Graph Box( Y Scale( LR, HR ), X Scale( LYH, HYH ), Yname( "Residuals" ), Xname( "Pred Y" ), Frame Size( 250, 120 ), Line( {LYH, 0}, {HYH, 0} ), Marker( Marker State( 0 ), fitvalues, Resids ) ) ) ), Outline Box( "Smoother and Linear leverage plots", Picture Box( SmPl ) ) ) ), Outline Box( "Summary of Fit", Table Box( String Col Box( , {"adj. R-square", "Deviance", "Number of Obs."} ), Number Col Box( , genfit ) ) ), Outline Box( "Parametric terms estimates", Table Box( String Col Box( "Term", pterms ), Number Col Box( "Estimate", pest ), Number Col Box( "Std Error", pstderr ), Number Col Box( "Prob.", pprob ), ) ), Outline Box( "Smoothed terms estimates", Table Box( String Col Box( "Term", sterms ), Number Col Box( "Est. df", sedf ), Number Col Box( "Ref df", srdf ), Number Col Box( "F", sf ), Number Col Box( "Prob.", sprob ), ) ) ); If( cw == 0, nw << close window ); ) ) ) ) ); ... View more

Dear Raewdy,   Unfortunately, this has nothing to do with the script, it is a limitation of the JMP R integration functions. Only JMP can fix that. Presumably, they will fix it in the next version of JMP... That being said, you can have multiple versions of R on your computer, including R 3.3.3.   Regards, Yves ... View more

Hi mujahida,   In response to your question, the spline function is not a simple mathematical function, it involves a series of coefficients  that change along the X according to certain intervals. It is not practical to export a matrix of coefficients.   Regards, Yves ... View more

Hello Mujahida,   First of all, sorry for the delay in responding. I don't quite understand what is happening because the function works well for me. What version of JMP are you using?    Best regards, Yves ... View more

Hi Marxx,   This is strange. It is as if the subtraction is evaluated before the matrix multiplication, which it shouldn't.   Look for line 219 and add a set of parenthesis as in lsres = ym - (axm * lsbetas);   It turns out tht this line is not really needed anyway and is a relict of a previous script. You  could also simply delete lines 219, 220 and 225 (or put // at the beginning of each). Try that and let me know. Yves   ... View more

It is uploaded now. If you can think of little features you would find useful, let me know. Yves ... View more

HI marxx,   I haven't tested it on many platforms but it is not using anything fancy so I don't see why it would not work on JMP13 on Windows (I used JMP14 Pro on a Mac). One thing you could do is open the embedded JSL file and simply run it as a script. You might get more info in the log window as to what is not working. I include here a little screen capture video showing what it is supposed to do.   Let me know if I can help you more. Yves   ... View more