similar to: Nolinear mixed-effects models (nlme)

Hello, I am trying to fit a nonlinear model of the form of: A*x^b*exp(-c*x) This represents a lactation curve. I have a bunch of cows, so I want COW to be a random effect. I have been trying the following code with very littel success: > fm1 <- nlme(yield ~ A*(DIM^B)*(exp(-C*DIM)), + data = group, + fixed = A + B + C ~ 1, + start = c(A = 20, B =

Hi, I need help writing a function I capture seal pups mutliple times during the lactation season in order to monitor their growth rate. When I release them, the recovery (mother-pup) time is not the same for all individuals. I want to know if individuals that recover their mother the fastest are the ones with the highest growth rates. So, I noted at every release if the pup

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

Hello Folks, Very new to R so bear with me, running 5.2 on XP. Trying to do a zero-inflated negative binomial regression on placental scar data as dependent. Lactation, location, number of tick larvae present and mass of mouse are independents. Dataframe and attributes below: Location Lac Scars Lar Mass Lacfac 1 Tullychurry 0 0 15 13.87 0 2 Somerset 0 0 0

Hi all, I'm a PhD student at sydney uni and am trying to run a non linear mixed model program to obtain estimates of parameters describing dairy cow lactation curves. At present, I have been able to get the data to converge using the S plus (S plus 2000) nlme function. However, when I put the same data into R (R 1.9.0), add in the nlme package and run the code, it does not converge by the

Hi all, I have considered neural network to classify the health status of the cow. I found a very neatly written R codes for classification method in here<http://home.strw.leidenuniv.nl/~jarle/IAC/RRoutines/classification-example.R> . It would be very helpful if you can answer some of the questions, that I am struggling with, I have set of time series data from different animals, I use

Cordial saludo adjunto la base de datos y el script: eu60<- read.csv(file.choose(), header=T, sep=";", dec=".", row.names=1) eu60.pca <- PCA(eu60, quali.sup=19) eu60.data <- cbind.data.frame(eu60[,19], eu60.pca$ind$coord) eu60.ellipse <- coord.ellipse(eu60.data, bary=TRUE) plot.PCA(ellipse=eu60.ellipse, cex=0.8) El 4 de diciembre de 2013 17:35, Camilo Calle

Hola, ¿qué tal? Tu problema es que tienes agrupaciones de países (p.e., ASIA_MERIDIOL) con un solo respresentante. Las matrices con las que construyes las elipses son degeneradas (más bien, no existen: sospecho que tienen que ver con la covarianza... ¿de un único caso?). Elimina las agrupaciones triviales. Un saludo, Carlos J. Gil Bellosta http://www.datanalytics.com El día 4 de diciembre de

Cordial saludo, soy principiante en R y estoy haciendo un análisis multivariado de datos, y necesito hacer las elipses de confianza donde la variable 19 es cualitativa suplementaria y el resto son variables activas; tengo el siguiente código: eu60 <- read.csv(file.choose(), header=T, sep=";", dec=",", row.names=1) ### capturar datos eu60.pca <- PCA(eu60, quali.sup=19) ##

Hello, I try to do a very simple nonlinear regression. The function is y = (b0 + b1*x1 + b2*x2 + b3*x3) * x4^b4 I think I do everything well, but as I set the starting value of b4 to 0 (it is the theoretically sane starting value), it converges very quickly, and to the wrong solution. Wrong in a sense, that 1) we do not expect this and 2) we do not get this on E-Views, Stata and SAS. I do not

Mª Luz, si el comando de Carlos te devuelve 0 es que no hay NA's. Da igual que tus columnas sean caracteres o número. Lo que intuyo es que tienes celdas con la frase "NA" que interpretas como NA. Mandanos el summary de tu data.table y lo vemos... ----- Mensaje original ----- De: "MªLuz Morales" <mlzmrls en gmail.com> Para: "Carlos J. Gil Bellosta"

Dear all, Here is my code which am using to combine 5th column from different data sets. Here is the function to do my job genesymbol.append.file <-NULL gene.column <- NULL readGeneSymbol <- function(files,genesymbol.column=5){ for(i in fnames){ temp <- read.table(fnames,header=T,sep="\t",stringsAsFactors=F,quote="\"")