Although I am not an expert in NLME modelling, looking at your data it seems to me that there seems to be no growth pattern in it. Try
library(nlme) library(reshape) goat<-read.table("clipboard", header=T) > str(goat) 'data.frame': 18 obs. of 15 variables: $ NoC : int 52 48 54 60 58 42 44 47 50 56 ... $ PL1 : int 490 970 1450 620 1370 1200 1200 1000 1300 950 ... $ PL2 : int 950 1020 1420 1250 1350 920 1560 1100 1150 1250 ... $ PL3 : int 800 980 1430 1100 1200 1150 1650 1000 1200 1200 ... $ PL4 : int 900 740 1120 1150 1300 850 1600 870 1030 1280 ... goat.m <- melt(goat, id="NoC") levels(goat.m$variable) <- 1:14 goat.m$variable <- as.numeric(as.character(goat.m$variable)) names(goat.m)[2] <- "week" goat.m$NoC <- ordered(goat.m$NoC) goat.g <- groupedData(value~week|NoC, data=goat.m) plot(goat.g) But maybe I am completely mistaken. Regards Petr [EMAIL PROTECTED] napsal dne 04.09.2007 18:02:09: > > Greetings R Help Group, > > How does one effect a multiphasic logistic growth model with 4 phases (e.g. > Koops 1986; Weigel, Craig, Bidwell and Bates 1992; Grossman and Koops 2003) with R. > > Before writing to the group, the R help archives were searched, the web was > searched with Google, Venables and Ripley 2002 was consulted, Pinheiro and > Bates 2000 was consulted, Bates and Watts 2007 was bought and consulted, ETC. > but to no avail. > > I have not written to any other group with respect to this problem. > > The following data are offered as an example of the type of problem I am > dealing with and are average daily goat milk production in ml. for 14 weeks. > NoC is the goat number. PL1 is the production during the first week; PL2 is > the production during the second week, etc. > > NoC PL1 PL2 PL3 PL4 PL5 PL6 PL7 PL8 PL9 PL10 PL11 PL12 PL13 PL14 > 52 490 950 800 900 850 850 750 610 640 900 980 890 890 910 > 48 970 1020 980 740 1050 970 850 790 900 920 1120 1120 1030 1300 > 54 1450 1420 1430 1120 1330 1230 1030 1170 1350 1530 1490 1500 1310 910 > 60 620 1250 1100 1150 780 930 990 940 760 730 790 1050 840 850 > 58 1370 1350 1200 1300 1350 1310 1070 910 1010 1300 1110 1070 990 660 > 42 1200 920 1150 850 720 630 630 710 850 810 930 980 820 1570 > 44 1200 1560 1650 1600 1450 1600 1160 1010 1440 1450 1530 1500 1550 850 > 47 1000 1100 1000 870 760 900 820 865 910 820 930 900 1130 1070 > 50 1300 1150 1200 1030 1070 970 860 900 950 1190 1250 1130 800 1400 > 56 950 1250 1200 1280 1220 1155 840 1016 1370 1220 1570 1520 1500 1150 > 1 870 1250 1160 1270 1200 1410 1110 1008 970 1130 1490 1330 1320 820 > 3 1000 1100 1200 1120 1250 980 750 890 1050 1160 1340 1210 1150 760 > 4 551 760 550 580 540 620 550 520 470 720 680 790 750 1230 > 5 810 1100 820 950 930 830 850 650 810 1070 1120 1300 1040 1320 > 6 800 1000 620 850 750 670 660 620 600 610 760 900 758 1070 > 7 720 830 1120 1050 820 820 850 810 800 750 780 940 1050 1310 > 8 950 1550 1560 1500 1230 1330 1150 1005 1020 1200 1440 1400 1290 1080 > 10 660 850 1100 980 1070 1100 870 790 880 950 1000 1210 1050 1220 > > It seems to me that it should be possible to effect the modeling process with > nlme. Any suggestions and or recommendations would be greatly appreciated. > > Peter B. > > > > Douglas M. Bates and Donald G. Watts. 2007. Nonlinear Regression Analysis and > Its Applications. Wiley Series in Probability and Statistics. John Wiley & > Sons, Inc., New York, NY, USA. > > M. Grossman and W.J. Koops. 2003. Modeling Extended Lactation Curves of Dairy > Cattle: A Biological Basis for the Multiphasic Approach. J. Dairy Sci. 86:988-998. > > W. J. Koops. 1986. Multiphasic Growth Curve Analysis. Growth 50:169-177. > > Jose C. Pinheiro and Douglas M. Bates 2000. Mixed-Effects Models in S and S- > Plus. Statistics and Computing. Springer-Verlag New York, New York, NY, USA. > > W. H. Venables and B. D. Ripley. 2002. Modern Applied Statistics with S. > Fourth edition. Statistics and Computing. Springer-Verlag New York, Inc., New > York, NY, USA. > > K. A. Weigel, B. A. Craig, T. R. Bidwell and D. M. Bates. 1992. Comparison of > Alternative Diphasic Lactation Curve Models under Bovine Somatotropin > Administration. J. Dairy Sci. 75:580-589. > > > > > > > Peter B. Mandeville cel: 444 860 3204 tel: 52 444 826 2346-49 ext 532 > fax: 52 444 826 2352 P.D. Favor de confirmar la llegada de este correo. Gracias. > _________________________________________________________________ > Discover the new Windows Vista > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.