similar to: How to evaluate sequence of strings like this

Hi, here i have a Max and Min values Min <-3 Max <-6 and also a matrix like this, ABC XYZ PQR ------ ------- ------- 2 4 3 5 4 8 7 1 3 In this i need to check each particular column values are between Max and Min value. If the coulmn value not coming between Max and

Hi Guys, stumped by a simple problem. I would like to take a file of the form Pair group param1 1 D 10 1 D 10 1 R 10 1 D 10 2 D 10 2 D 10 2 D 10 2 R 10 2 R 10 etc.. and for each pair, calculate the average of

Dear all, I am estimating a mixed-model in Ubuntu Raring (13.04¸ amd64), with the code: fm0 <- lme(rt ~ run + group * stim * cond, random=list( subj=pdSymm(~ 1 + run), subj=pdSymm(~ 0 + stim)), data=mydat1) When I check the approximate variance-covariance matrix, I get: > fm0$apVar [1] "Non-positive definite

Hello, Hope that someone could help me plotting longitudinal data below: 7213 3333330001 0.8300 13.05.09 1 1 3333330001 0.8700 09.02.05 NULL 4797 3333330001 0.7700 21.03.07 NULL 2399 3333330001 0.7800 12.04.06 NULL 2400 3333330002 NULL 27.03.06 NULL 7230 3333330002 0.8200 14.05.09 0 2 3333330002 0.8400 09.02.05 NULL 4798 3333330002 0.8700 20.03.07 0 4799 3333330003 0.9000 20.03.07 13 2401

Hi, I am new in R, i have a matrix like this MyMatrix <- *ABC PQR XYZ* 10 20 30 40 50 60 70 80 90 And, i have an array containing some conditions like this, MyArray <- c("*ABC*>50","*PQR*<50","*ABC*<30 &* XYZ*<40") "ABC>50" "PQR<50" "ABC<30 & XYZ<40"

I have a new problem: Register RBP is used in a function foo. (I am not allocating RBP to any virtual register, the instances of RBP in function foo are in the machine code when my register allocator starts.) Function foo calls function bar. Register RBP is not saved across the call, though it is live after the call. Function bar includes a virtual register. The code that I'm using to

Hi R Fans, I stumbled across a strange (I think) bug in R 2.9.1. I have read in a data file with 5934 rows and 9 columns with the commands: daten = data.frame(read.table("C:/fussball.dat",header=TRUE)) Then I needed a subset of the data file: newd = daten[daten[,1]!=daten[,2],] --> two values do not meet the logical specification and are dropped. The strange thing about it:

 Hi:  Using nls how can I increase the numbers of iterations to go beyond 50.  I just want to be able to predict for the last two weeks of the year.  This is what I have:  weight_random <- runif(50,1,24)  weight <- sort(weight_random);weight weightData <- data.frame(weight,week=1:50)                          weightData plot(weight ~ week, weightData) M_model <- nls(weight ~ alpha +

Dear All   I have the following code set up: Code #1 a <-matrix(seq(0,8, by = sign(8-0)*0.25)) b <-matrix(seq(8,16, by = sign(16-8)*0.25)) c <-runif(1000,50,60) d <-exp(-c*a)+exp(-c*b)   This will give me the obvious error message of lengths not matching. What I am trying to do here is to have 33 rows x 1000 columns d values calculated in total. As an eaxmple for visual, this is what

?s 17:38 de 30/11/2023, Robert Baer escreveu: > I am having trouble using back ticks with the R extractor function > 'predict' and an lm() model.? I'm trying too construct some nice vectors > that can be used for plotting the two types of regression intervals.? I > think it works with normal column heading names but it fails when I have > "special"

Hi, I'm using a loop to evaluate several models by taking adjacent variables from my dataframe. When i try to get predictions for new values, i get an error message about a missing variable in my new dataframe. Below is an example adapted from ?gam in mgcv package library(mgcv) set.seed(0) n<-400 sig<-2 x0 <- runif(n, 0, 1) x1 <- runif(n, 0, 1) x2 <- runif(n, 0, 1) x3 <-

Dear R experts Sorry for this question M1 <- 1:10 lcd1 <- c(11, 22, 33, 44, 11, 22, 33, 33, 22, 11) lcd2 <- c(22, 11, 44, 11, 33, 11, 22, 22, 11, 22) lcd3 <- c(12, 12, 34, 14, 13, 12, 23, 23, 12, 12) #generating variables through sampling pvec <- c("PR1", "PR2", "PR3", "PR4", "PR5", "PR6", "PR7",

Hey List, I did a multiple regression and my final model looks as follows: model9<-lm(calP ~ nsP + I(st^2) + distPr + I(distPr^2)) Now I tried to predict the values for calP from this model using the following function: xv<-seq(0,89,by=1) yv<-predict(model9,list(distPr=xv,st=xv,nsP=xv)) The predicted values are however strange. Now I do not know weather just the model does not fit

I am having trouble using back ticks with the R extractor function 'predict' and an lm() model.? I'm trying too construct some nice vectors that can be used for plotting the two types of regression intervals.? I think it works with normal column heading names but it fails when I have "special" back-tick names.? Can anyone help with how I would reference these?? Short of

Dear all,? I hope that you can help me on this. I have been struggling to figure this out but I haven't found any solution. I am running a generalised mixed effect model, gamm4, for an ecology project. Below is the code for the model: model<-gamm4(LIFE.OE_spring~s(Q95, by=super.end.group)+Year+Hms_Rsctned+Hms_Poaching+X.broadleaved_woodland? ? ? ? ? ? ?+X.urban.suburban+X.CapWks,

Here's my little discussion example for a quadratic regression: http://pj.freefaculty.org/R/WorkingExamples/regression-quadratic-1.R Students press me to know the benefits of poly() over the more obvious regression formulas. I think I understand the theory on why poly() should be more numerically stable, but I'm having trouble writing down an example that proves the benefit of this. I

Dear all, I have got two vectors coding for a stimulus presented in the current trial (mydat$Stimulus) and a prediction in the same trial (mydat$Prediciton), respectively. By applying an if-conditional I want to create a new vector that indicates if there is a match between both vectors in the same trial. That is, if the prediction equals the stimulus. When I pick out some trials randomly, I get

Thank you Jim, I read the data as you suggested but I could not find K1 in col1. rbind(preval,mydat) Col1 Col2 col3 1 <NA> <NA> <NA> 2 X1 <NA> <NA> 3 Y1 <NA> <NA> 4 K2 <NA> <NA> 5 W1 <NA> <NA> 6 Z1 K1 K2 7 Z2 <NA> <NA> 8 Z3 X1 <NA> 9 Z4 Y1 W1 On Sat, Feb 24, 2018 at 6:18 PM, Jim

Good day everyone, Can anyone suggest an effective method to solve the following problem: I have 2 dataframes D1 and D2 as follows: D1: dates ws wc pwc 2005-10-19:12:00 10.8 80 81 2005-10-20:12:00 12.3 5 15 2005-10-21:15:00 12.3 3 15 2005-10-22:15:00 11.3 13 95 2005-10-23:12:00 12.3 13 2 2005-10-24:15:00 10.3 2 95 2005-10-25:15:00 10.3 2 2 D2:

Hi Val, My fault - I assumed that the NA would be first in the result produced by "unique": mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) val23<-unique(unlist(mydat[,c("Col2","col3")])) napos<-which(is.na(val23)) preval<-data.frame(Col1=val23[-napos],