search for: tepl

...x of predict.nlme. I would like to predict from nlme object for new data. I used predict(fit.nlme6, data=newdata) but I have always got fitted values, no matter how I changed newdata. I have > summary(fit.nlme6) Nonlinear mixed-effects model fit by maximum likelihood Model: konverze ~ SSfpl(tepl, A, B, xmid, scal) Data: limity.gr AIC BIC logLik 882.4939 907.6738 -433.2469 Random effects: Formula: list(xmid ~ 1, scal ~ 1) Level: spol.f Structure: General positive-definite, Log-Cholesky parametrization StdDev Corr xmid 29.680114 xmid scal 6.481...

...elsq2wbl [elsq2wbl[, "EVERRELJOB"] < -3, "EVERRELJOB"] <- NA > elsq2wbl [elsq2wbl[, "PSWBL"] < -2, "PSWBL"] <- NA If you wanted recode values below zero to NA you can do this easily without any ifelse > summary(test) mp tepl kryst Min. : 7.11 Min. :100.0 Min. : 21.70 1st Qu.:32.25 1st Qu.:400.0 1st Qu.: 24.15 Median :37.50 Median :500.0 Median : 26.55 Mean :38.44 Mean :485.7 Mean : 42.64 3rd Qu.:44.75 3rd Qu.:600.0 3rd Qu.: 33.62 Max. :76.02 Max. :900.0 Max. :15...

Hello R-Users, I have the following problem with the subset function: See the following simple linear model. Here everything works fine: >germany<-lm(RENT~AGE1, in.mi01) However, if a use the same regression equation and only specify a subset, I get an error message: > berlin<-lm(RENT~AGE1, in.mi01, subset=C_X01=="Berlin") Error in lm.fit(x, y, offset

Dear all I am trying nlme together with Pinheiro/Bates book. I constructed grouped data object with suitable plotting layout (according to some common factor, panels from bottom to top are in increasing order). When I do nlme(... some stuff...) I get fitted object which I can plot with plot(augPred(fit.nlme6, level=0:1)) but it results in completely different ordering. Is there any way

Hello R Help List, I am an R novice and trying to use the ifelse function to create a new binary variable based off of the responses of two other binary variables; NAs are involved. I pulled it off almost successfully, but when I checked the counts of my new variable for accuracy, I found that a small portion of the NA cases were not being passed through as NAs, but as "0" counts in my

This is probably a simple problem but I don't see a solution. I have a data.frame with a number of columns where I would like 0 <- NA thus I have df1[,144:157] <- NA if df1[, 144: 157] ==0 and df1[, 190:198] <- NA if df1[, 190:198] ==0 but I cannot figure out a way do this. cata <- c( 1,1,6,1,1,NA) catb <- c( 1,2,3,4,5,6) doga <- c(3,5,3,6,4, 0) dogb <- c(2,4,6,8,10,

Hi all, I'm having some trouble with rbind - this may be a bug or it may be my misunderstanding. If I do fileName <- paste(tempdir(),"test.txt",sep="/") file.create(fileName) x <- read.table(fileName, col.names=c("one","two","three")) I get a data frame with no rows, as documented. If I then try to rbind this with another data frame

> On Aug 23, 2017, at 8:08 AM, PIKAL Petr <petr.pikal at precheza.cz> wrote: > > Hi > > Well, yes I tried it about two weeks ago but my post did not get through as it still awaits moderator approval. It got through just fine. It appeared on Aug 15. It just didn't get any replies. As I read your original question in this thread, it was not clear to me that you had

Hi Well, yes I tried it about two weeks ago but my post did not get through as it still awaits moderator approval. I could check which column is offending but actually it is only minor nuisance, I can live with selection of columns before fitting a model. What seems to me strange is that both full dataset and only selected colums gave me identical fit results but only one works within augPred.