similar to: can I get same results using lme and gls?

I was reading the help but just did not get how to specify starting values for varIdent() of the lme() function, although I managed to do it for corSymm(). Do I specify the values just as they are printed out in an output, like c(1, 1.3473, 1.0195). Or do I need to take the residual and multiply it with these like c(0.2235, 0.2235*1.3473, 0.2235*1.0195) or any other form that I dont know of?

Hi Folks, I have just started using dplyr and could use some help getting unstuck. It could well be that dplyr is not the package to be using, but let me just pose the question and seek your advice. Here is my basic data frame. head(h) subject ageGrp ear hearingGrp sex freq L2 Ldp Phidp NF SNR 1 HALAF032 A L A F 2 0 -23.54459 55.56005 -43.08282

Hello all, I have a .csv file like below. Tool,Step_Number,Data1,Data2... etc up to 100 columns. A,1,0,1 A,2,3,1 A,3,2,1 . . B,1,3,2 B,2,1,2 B,3,3,2 . . ...... so on upto 50 rows where the column "*Tool*" has distinct steps in second column "*Step_Number*",but both have same entries in Step_Number column. I want the output like below.

Do I miss here something? dtaa = read.table("http://www.ats.ucla.edu/stat/mplus/examples/ma_snijders/mlbook1.dat", sep=",") head(dtaa) # shows the data as it should be save(dtaa,"dtaa",file="c:/dtaa") d = load("c:/dtaa") head(d) # all data is lost, it only shows [1] "dtaa" "dtaa" Thanks for your hint on this.

Rows are horizontal, columns are vertical. You really need to spend some time with an R tutorial. dta <- read.table( "yourfile", header=TRUE, as.is=TRUE ) dta2 <- dta dta2$D <- c( "awe", "abcd", "asdf", "xyz" ) dta2 <- dta2[ , c( "A", "D" ) ] -- Sent from my phone. Please excuse my brevity. On June 22, 2017

Hi all - (this is posted to r-help and R-SIG-MAC) OSX 10.3.7, R 2.0.1, lme4/Matrix/latticeExtra latest, fresh install of R. MASS loaded (or not). I am getting an error message for the print() and summary() commands with all lme models I try and run in lme4 (GLMM's work fine). Using the example from the lme help, summary and print produce the following errors, despite the model being

I'm sorry for the really vague subject line but I am not sure how to succinctly describe what I am doing and what the problem is. But, here goes: 1. I have data with two-way data with frequencies. Below is an example, though in reality I am looking at about 10 different variables that I am crossing so the values of X1 and X2 change. X1 and X2 are place holders. Here's the dataset

Dear list, i am a student of psychology and have to do a multilevelanalysis on some data. About that i have one general and one specific question. This is what i have copied from the help-file on lme: data(bdf) fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf, random = ~ IQ.ver.cen | schoolNR) summary(fm) after summary(fm) i get the following error:

It is not generally advisable to get too fancy with stat functions in ggplot... things can easily get more complicated than ggplot is ready to handle when it comes to calculations. It is better to create data that corresponds directly to the graphical representations you are mapping them to. Read [1] for more on this philosophy. [1] H. Wickham, Tidy Data, Journal of Statistical Software,

On Thu, 26 Oct 2017, Thomas Adams wrote: > Hi Jeff, > > Thank you for the suggestions -- I appreciate your help. Unfortunately, the > result2 has two problems... > > (1) there are now 3 date columns (it looks like 2 cols are merged into 1 > col) No, there are two date columns. Result2 includes the grouping value as a row name (pulled from the names of the dta2list items

(See DAAG book, p. 173, ex. 3) I'm a new user of R, and I'm following the DAAG text. I want to create a subset of the races2000 data frame, but get errors because of a mismatch of values in some columns: > library(DAAG) > attach(races2000) > hills2000 <- races2000[races2000$type == 'hill'] Error in as.matrix.data.frame(x) : dim<- : dims [product 770] do not

If anyone has a few extra CPU cycles to spare, I'd appreciate it if you could verify a problem that I have encountered. Run the code below and tell me if it crashes your R before completion. library(lme4) data(bdf) dump<-sapply( 1:50000, function(i) { fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf, random = ~ IQ.ver.cen | schoolNR); cat("

Dear R-Users, I am currently working with LME to analyse repeated measures data. I encounter a problem when including both a random effect and a correlation structure with different grouping levels into the LME model. The error message is: Error in lme.formula(diameter ~ flowers*timef + competition*timef + population*timef, : Incompatible formulas for groups in "random" and

I have spent hours on R in Windows 7. Just installed 2 days ago so the R package should be current. Currently I am using the RGui (64-bit) for Windows. I can not read an Excel file into R from my computer. Have hours on this. Completely crazy!! I have the XLConnect package loaded. I think it is loaded because when I enter: > loadedNamespaces() [1] "base"

Dear all, I am planning to use nlme library for analysis of experiments in semiconductor industry. Currently I am using "lm" but plan to move to "lme" to handle within wafer / wafer-to-wafer and lot-to-lot variation correctly. So far everything is working well, but I have a fundamentel question: NLME offers "maximum likelihood" and "restricted maximum

Hi Jeff, Thank you for the suggestions -- I appreciate your help. Unfortunately, the result2 has two problems... (1) there are now 3 date columns (it looks like 2 cols are merged into 1 col) (2) the output rows should not have any of the basistime dates repeated (maybe I misstated the problem); I need the max fcst value by basistime, but also list the date value for that row; for example:

Thanks for the dput... #### reproducible example of split-apply-combine ### dta <- structure(list(date = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L), .Label = c("2012-01-25 18:00:00",

Can anyone help explain to me why the two codes below have different result? I thought I can use log(time)~. to replace log(time)~dist+climb+timef.I am using CVlm from DAAG package. I think nihills is preloaded with the package. Thanks in advance. > CVlm(df=nihills, form.lm=formula(log(time)~.),plotit="Observed",m=2)Analysis of Variance Table Response: log(time) Df Sum Sq

Hi, I am using Spark and the Sparklyr library in R. I have a file with several lines. For example A B C awer.ttp.net Code 554 abcd.ttp.net Code 747 asdf.ttp.net Part 554 xyz.ttp.net Part 747 I want to split just column A of the table and I want a new row added to the table D, with values awe, abcd, asdf, and xyz. I am trying to use a command in

Dear all, I have a data (bellow) and I want to make a correlation test with p-value structure(list(Name = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("CTJ", "PKR", "TTK"), class = "factor"), score = c(86.4371428571428, 89.7028571428572, 87.728, 89.99, 89.42, 85.6914285714286, 82.256,