similar to: having problems with the lme function

Hello everybody, I recently wrote a "program" that to generate AR1 time series, here the code: #By Jomopo. Junio-2007, Leioa, Vizcaya #This program to create the AR1 syntetic series (one by one) #Where the mean is zero, but the variance of the serie AR1 and #the coef. of AR1 are be changed. If var serie AR1 = 1 then is standarized! #Final version for AR1 time series program #Mon Jul

Dear all, I have a problem that may be someone of you can help. I am a newbie and do not find how to do it in manuals. I have two arrays, for example: ar1 <- array(data=c(1:16),dim=c(4,4)) ar2 <- array(data=c(1:16),dim=c(4,4)) colnames(ar1)<-c("A","B","D","E") colnames(ar2)<-c("C","A","E","B") > ar1

Hi, A quick question: I have to vectors, say ar1 and ar2 > ar1 [1] "a" "c" "c" "a" attr(,"levels") [1] "a" "b" "c" > ar2 [1] TRUE TRUE FALSE TRUE > table(ar1, ar2) ar2 ar1 FALSE TRUE a 0 2 c 1 1 I would like to obtain: T F a 2 0 b 0 0 c 1 1

Dear "R-listers" I've been trying to figure out how to annotate charts in ggplot (ie add text to line charts, highlighted boxes etc). By and large, I can get close to what i want with base graphics, but would ideally like to use ggplot whenever possible (additionally, i would like to add text labels automatically to the chart). The code is below I suspect I need to use geom_rect,

Windows 10 64-bit, R-Studio, R version 3.4.3 Several questions relating to groupedData: (1) I am trying to create a groupedData object that can be used to run an analysis that I have been able to urn using lmer. When I include the interaction terms in the groupedData opbject I get an error message stating that + is not meaningful for factors. How do I include factors in my model? See code and

Dear R-help, I am trying to create groupedData objects using the nlme library. I'm missing something basic, I know: Here is the first example in ch.1 of Pinheiro & Bates (2000): library(nlme) x2=Rail$travel;x1=Rail$Rail;eg1=data.frame(x1,x2);eg1gd=Rail print(eg1gd) x11();print(plot(eg1gd)) femodel=lm(x2~x1-1,data=eg1gd) print(femodel$coefficients) Result: x12 x15 x11

help.search("groupedData") says that it's part of the lme4 package, but it appears not to be there (details below). Is this because lme4 is new and (perhaps) still under development? > update.packages() trying URL `http://cran.r-project.org/bin/windows/contrib/1.9/PACKAGES' Content type `text/plain; charset=iso-8859-1' length 19113 bytes opened URL downloaded 18Kb >

Dear all, I am trying (!!!) to generate pdfs that have 8 plots on one page: df = data.frame( day = c(1,2,3,4), var1 = c(1,2,3,4), var2 = c(100,200,300,4000), var3 = c(10,20,300,40000), var4 = c(100000,20000,30000,4000), var5 = c(10,20,30,40), var6 = c(0.001,0.002,0.003,0.004), var7 = c(123,223,123,412), var8 = c(213,123,234,435), all = as.factor(c(1,1,1,1)))

Hello I am trying to fit a REML to some soil mineral data which has been collected over the time period 1999 - 2004. I want to know if the 19 different treatments imposed, differ in terms of their soil mineral content. A tree model of the data has shown differences between the treatments can be attributed to the Magnesium, Potassium and organic matter content of the soil, with Magnesium being the

I'm using groupedData from nlme. I set up a groupedData data.frame with outer=~group1. When I try to plot with outer=TRUE, I get "subscript out of bounds." This happens most of the time. When it works, I get spaghetti-type plots for comparing groups. But I don't understand why it doesn't usually work. > longa.mod.1.gd <- groupedData(mod1.logit~time|

Hello, I'm an R newbie. I've tried to search, but my search skills don't seem up to finding what I need. (Maybe I don't know the correct terms?) I need the standard errors and not the confidence intervals from an ARIMA fit. I can get fits: > coef(test) ar1 ma1 intercept time(TempVector) - 1900

Dear John You are only allowed to have the primary covariate on the left hand side of the vertical bar. Other covariates go in inner or outer. Michael On 22/03/2018 12:59, Sorkin, John wrote: > Windows 10 64-bit, R-Studio, R version 3.4.3 > > > Several questions relating to groupedData: > > (1) I am trying to create a groupedData object that can be used to run an analysis

Hello, I'm trying to use the groupedData function and R is giving me the message: Error: can not find function "groupedData" The code is coming from a textbook so I think it should be correct: pigs<-data.frame(cbind(pig.time,pig.id,pig.wt)) pig.growth<-groupedData(pig.wt~pig.time|pig.id,data=pigs) I have added the package "nlme" and to confirm that it was installed

Dear Group: I have been trying to write an R function within which the function groupedData() would be used. The following is a sample program: ####################### sid<-rep(1:6,times=2) time<-c(1:12) trt<-rep(letters[1:3],times=4) tem<-data.frame(sid,time,trt) test1.fun<- function(dat=dat) { groupedData(time ~ trt|sid, data=dat) } test1.fun(dat=tem)

I am encountering difficulty with NextMethod in 0.50-a4. We created a class of groupedData objects which are data.frames with additional attributes. The most important attribute is a formula describing roles of some of the variables in the experimental design. The class of such objects ends in "groupedData", "data.frame". The print method for the groupedData class simply

Hi,   I have an original data frame with 8 columns of variables, which are stored in 'data1' frame.   data1 <- read.csv("E:\\PHD GLASGOW UNIVERSITY\\Data\\R\\Colin\\Cailness21.csv") attach(data1) names(data1)   [1] "Date"       "d"          "m"          "y"          "Time"      [6] "Depth"      "Temp"      

Hi, I'm running GEE using geepack. I set corstr = "ar1" as below: > m.ar <- geeglm(L ~ O + A, + data = firstgrouptxt, id = id, + family = binomial, corstr = "ar1") > summary(m.ar) Call: geeglm(formula = L ~ O + A, family = binomial, data = firstgrouptxt, id = id, corstr = "ar1") Coefficients:

Hi everyone. I am trying to add a formula to my data using the groupedData function. My experiment consists of randomized block design using fruits, vegetation and time as factors. The idea is to see if fruits, vegetation and time explain the abundance of mice. I am using tree density as a covariate. So I tried to fit the following structure to my data. >

I measured nitrate concentration and primary production (PP) biweekly for 23 months in one headwater stream. I would like to use linear regression to determine if PP is related to nitrate concentration. My dataframe is called "data" and consists of the vectors Rdate, PP, and nitrate. Rdate is the observation date in class "date" and PP is primary production. I first

Sorry - I suspect this is a very basic query. I have a data frame structured "flat" (i.e. separate observations for a given subject ID on separate lines). Using the nlme library I create a groupedData object suitable for further analysis thus: dataset <- groupedData(VARIABLE ~ TIME|ID, data=sfa) The dataset has a large number of VARIABLES of interest so I want to make use of loops