similar to: Best and Worst values

Hello All, I would like to optimize a (log-)likelihood function subject to a number of linear constraints between parameters. These constraints are equality constraints of the form A%*%theta=c, ie (1,1) %*% 0.8,0.2)^t = 1 meaning that these parameters should sum to one. Moreover, there are bounds on the individual parameters, in most cases that I am considering parameters are bound between zero

Hi, I guess you meant this: dat2<- read.table(text=" patient_id????? t???????? scores 1????????????????????? 0??????????????? 1.6 1????????????????????? 1??????????????? 2.6 1????????????????????? 2???????????????? 2.2 1????????????????????? 3???????????????? 1.8 2????????????????????? 0????????????????? 2.3 2?????????????????????? 2???????????????? 2.5 2?????????????????????

Hi, dat1<- read.table(text=" Restaurant owner purchase_date ??????????? 23 Chuck 3/4/2011 ??????????? 23 Chuck 3/4/2011 ??????????? 23 Chuck 3/4/2011 ??????????? 23 Chuck 3/4/2011 ??????????? 23 Bob??????? 1/1/2013 ??????????? 23 Bob??????? 1/1/2013 ??????????? 23 Bob???????? 1/1/2013 ??????????? 15 Hazel 4/11/2010 ??????????? 15 Hazel 4/11/2010 ??????????? 15 Hazel 4/11/2010 ???????????

Hi, (Please use ?dput() to share the example dataset. Avoid using images to show dataset. Also, please read the posting guide esp. regarding home work, assignments etc.) res <- sapply(Gene[,-1],function(x) tapply(x,list(Gene$Genotype),mean)) #or res2 <-? aggregate(.~Genotype, data=Gene,mean) #or library(plyr) ?res3 <- ddply(Gene,.(Genotype),numcolwise(mean)) identical(res2,res3)

Muchas gracias a ambos Carlos y Jorge por las respuestas. Pido disculpas en la demora de respuesta, pero estuvo complicada la semana. La pregunta era un ejercicio de ejemplo para poder entender mejor los usos, creo que me armaré una guía en markdown con ejemplos varios para ir consultando cuando me salgan dudas de como usarlos. En realidad no importaba tanto si mejorara demasiado los tiempos

Hello, I am using Dr. Harrell's design package to make a nomogram. I was able to make a beautiful one without stratifying, however, I will need to stratify to meet PH assumptions. This is where I go wrong, but I'm not sure where. Non-Stratified Nomogram:

Hi, Your question is still not clear. May be this helps: dat2<- read.table(text=" patient_id????? t???????? scores 1????????????????????? 0??????????????? 1.6 1????????????????????? 1??????????????? 2.6 1????????????????????? 2???????????????? 2.2 1????????????????????? 3???????????????? 1.8 2????????????????????? 0????????????????? 2.3 2?????????????????????? 2???????????????? 2.5

Hi, directory<- "/home/arunksa111/data.new" #first function filelist<-function(directory,number,list1){ setwd(directory) filelist1<-dir(directory) direct<-dir(directory,pattern = paste("MSMS_",number,"PepInfo.txt",sep=""), full.names = FALSE, recursive = TRUE) list1<-lapply(direct, function(x) read.table(x,header=TRUE, sep =