Good Day, Included below is some code to generate data and to fit a mixed effects model to this fake data. The code works as expected when I call the function "lme" in Splus but not in R.
The error message from calling lme in R is: "Error in getGroups.data.frame(dataMix, groups) : Invalid formula for groups" I installed the nlme package for R around 20 August 2003. Thanks in advance. System information: Splus: Version 6.1.2 Release 2 for Sun SPARC, SunOS 5.6 : 2002 R: platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 7.1 year 2003 month 06 day 16 language R ############## BEGINNING OF CODE ########################### # a fake dataset to make the bumps with nn <- 30 # of data points mm <- 7 # number of support sites for x(s) # create sites s ss <- seq(1,10,length=nn) # create the data y e1 <- rnorm(nn,sd=0.1) e2 <- cos(ss/10*2*pi*4)*.2 yy <- sin(ss/10*2*pi)+e2+e1 plot(ss,yy) # locations of support points ww <- seq(1-2,10+2,length=mm) # width of kernel sdkern <- 2 # create the matrix KK KK <- matrix(NA,ncol=mm,nrow=nn) for(ii in 1:mm){ KK[,ii] <- dnorm(ss,mean=ww[ii],sd=sdkern) } # create a dataframe to hold the data df1 <- data.frame(y=yy,K=KK,sub=1) df1$sub <- as.factor(df1$sub) # now fit a mixed model using lme a1 <- lme(fixed= y ~ 1, random= pdIdent(~KK-1), data=df1,na.action=na.omit) # obtain and plot the fitted values a1p <- as.vector(predict(a1,df1)) lines(ss,a1p,lty=1) ##################### END OF CODE ######################################3 -- ********************************************************************* | Michael Fugate Temp Phone: (505) 665-1817 | | Statistical Sciences Group, D-1 | | Los Alamos National Laboratory email: [EMAIL PROTECTED] | | Los Alamos, NM 87545 | | Mail Stop: F600 | ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help