similar to: Testing class variables

Dear all, This is what I'd like to do (I have an implementation using for loops, which I designed before I realised just how slow R is at executing them - this process currently takes days to run). I have a large dataframe containing corporate bond data, columns are: BondID Date (goes back 5years) Var1 Var2 Term2Maturity What I want to do is this: 1) For each bond, at each given date,

I''ve had a right fun few days at work trying to figure out why our Rails app (which isn''t under very heavy load) kept eating memory and bringing our server to our knees. Eventually I traced it to send_file (which was in a way a relief as it wasn''t down to my coding ;) -- every time a user started downloading, the memory consumed by the app would jump, and

Hi everybody, I'm trying to analyse a set of data with a non-normal response, 2 fixed effects and 1 nested random effect with strong heteroscedasticity in the model. I planned to use the function lmer : lmer(resp~var1*var2 + (1|rand)) and then use permutations based on the t-statistic given by lmer to get p-values. 1/ Is it a correct way to obtain p-values for my variables ? (see below)

Hi, I have two datasets stored in tab-separated format in the following way file1: country year1 year2 Germany var1 var1 Hungary var1 var1 file2: country year1 year2 Germany var2 var2 Hungary var2 var2 I can easily read in these files, but how can I merge them as a panel dataset? Thanks, Viktor

Dear R helpers Suppose I have a data.frame as given below - my_dat = data.frame(class = c("XYZ", "XYZ", "XYZ", "XYZ", "XYZ","ABC", "ABC", "ABC", "ABC", "ABC" ),  var1 = c(20, 14, 89, 81, 17, 44, 36, 41, 11, 36), var2 = c(1001, 250, 456, 740, 380, 641, 111, 209, 830, 920)) > my_dat    class

Dear List, I have Multi-level Data i= Indivitual Level g= Group Level var1= First Variable of interest var2= Second Variable of interest and I want to count the frequency of "var1" and "var2" on the group level. I found a way, but there must be a much simpler way. data.ml <- data.frame(i=c(1:8),g=as.factor(c(1,1,1,2,2,3,3,3)),var1=c(3,3,3,4,4,4,4 ,4),

Hi all, I am trying to run an lme4 model (logistic regression with mixed effects) in MCMCglmm but am unsure how to implement it properly. Currently, my lme4 model formula looks as follows: "outcome ~ (1 + var1 + var2 | study) + var1 + var2" In English, this means that I am fitting a random effects model, where the intercept, var1 and var2 are jointly distributed according to study.

I am new to R and new to time series modeling. I have a set of variables (var1, var2, var3, var4, var5) for which I have historical yearly data. I am trying to use this data to produce a prediction of var1, 3 years into the future. I have a few basic questions: 1) I am able to read in my data, and convert it to a time series format using 'ts.' data_ts <- ts(data, start = 1988, end =

Hi, Is there or could there be any way to test that a method calls "super"? Thanks -- Jonathan Leighton, Web Developer http://jonathanleighton.com/

Buenas noches Javier y José, Estoy en contra de usar attach(), asi que propongo la siguiente alternativa con with(): # paquete require(epicalc) # los argumentos en ... pasan de epicalc:::cc # ver ?cc para mas informacion foo <- function(var1, var2, var3, ...){ or1 <- cc(var1, var2, ...) or2 <- cc(var1, var3, ...) list(or1 = or1, or2 = or2) } # datos x <-

Hi all, I have been trying to solve this problem and have had no luck so far. I have numeric vectors VAR1, VAR2, and VAR3 which I am trying to cbind. I also have a character vector "VAR1,VAR2,VAR3". How do I manipulate this character vector such that I can input a transformed version of the character vector into cbind and have it recognize that I'm trying to refer to my numeric

Hola.. yo lo haría de la siguiente manera ... En excel:genero una columna con la serie de fechas continuas ... con la función buscarv, agrego las variables que tienen dato a esta serie.. en base a la fecha muy largo y mecánico para mi gusto.... En R ..de igual manera genero el vector de fechas require(chron)# crear el vector continuo de fechasfch01 <- data.frame(''fch'' =

Hi, I am using R 1.9.1 on on i686 PC with SuSE Linux 9.0. I have a data.frame, e.g.: > myData <- data.frame( var1 = c( 1:4 ), var2 = c (5:8 ) ) If I add a new column by > myData$var3 <- myData[ , "var1" ] + myData[ , "var2" ] everything is fine, but if I omit the commas: > myData$var4 <- myData[ "var1" ] + myData[ "var2" ] the name

I would like to know how to turn a variable into a string. I have tried as.symbol and as.name but it doesnt work for what I'd like to do Essentially, I'd like to feed the function below with two variables. This works fine in the bit working out number of elements in each variable. In the print(sprintf("OK with %s and %s\n", var1, var2)) line I would like var1 and var2 to be

Hello everyone, I am looking at the joint spatial distribution of 2 kinds of organisms (estimated on a grid of points) and want to test for significant association or dissociation. My first question is: do you know a nice technique to do that, considering that I have a limited number of points (36) but that they are repeated (4 times)? I did GLMs to test for correlations between the

G'day, I'm?calculating LSM for the following model, and am finding that R and SAS give different answers. Whilst the error is at the second or third decimal, the percentage error can be quite large. I'm using the effects library (Version: 2.0-10) on R?2.11.1 in the following manner: options(contrasts=c("contr.helmert","contr.poly"))

Dear List, I'm getting the error: object of type 'closure' is not subsettable And am not sure how to get around the problem. I've included two short code sets below. One that shows what I want to do and works, but without using the function much, and another that tries to use the function but causes the error. # THIS WORKS AND SHOWS WHAT I'D LIKE TO DO a <- c(1,2,3) b

HI R help, I was trying to get identical data frame from a list using two methods. #Suppose my list is: listdat1<-list(rnorm(10,20),rep(LETTERS[1:2],5),rep(1:5,2)) #Creating dataframe using cbind dat1<-data.frame(do.call("cbind",listdat1)) colnames(dat1)<-c("Var1","Var2","Var3") #Second dataframe conversion

Hi all, I analysed my data with lme and after that I spent a lot of time for mean separation of treatments (post hoc). But still I couldn’t make through it. This is my data set and R scripts I tried. replication fertilizer variety plot height 1 level1 var1 1504 52 1 level1 var3 1506 59 1 level1 var4 1509 54 1 level1 var2 1510 48 2 level1 var1 2604 47 2 level1 var4 2606 51 2 level1 var3

Dear R helpers I am resending my mail as the output I desire was not properly visible and I apologize for the same. Suppose I have a data.frame as given below - my_dat = data.frame(class = c("XYZ", "XYZ", "XYZ", "XYZ", "XYZ","ABC", "ABC", "ABC", "ABC", "ABC" ),  var1 = c(20, 14, 89, 81, 17, 44,