similar to: creating files using for loop

Thanks to the help of many on this list, I am now an R user and have been able to write some functioning code to do matching estimation. I have two for loops (i in 1:3, and j in 0:2). Within the loops, I had been creating matrices of relevant estimation coefficents in order to make lots of LaTeX tables. Well, now I want to be able to combine the results of many different estimations from within

I am using R for Unix and want to make some LaTeX tables. I have already played around in R for Windows and have succeeded in making tables that I want using the following code: latex(Estimates, file='out.tex', rowlabel='',digits=3) However, when I use this code in Unix, I can never find the file "out.tex". I assumed that R would send the file to whatever directory I

I have a dataset with 4 years of students, and normally I want to estimate things using each individual year, so I have a for loop as follows for (i in 1:4){} However, the only way I know how to calculate estimates using all four years of data is to put the estimations outside of the loop. Is there anyway to make a for loop that uses all four years at once, then uses each individual year?

Perhaps someone will have a solution to my more general problem, but here is the specific one: I used the round() function to round some estimates to 3 decimal places. I then sent put the rounded estimates in a matrix and used latex() to make a LaTeX table from them. However, in my table, there are estimtes which only have 2 decimal places. I assume that the third decimal place in these numbers

Dear R users, I am trying to become a convert to R (from Stata), and I'm having some growing pains. Is there anyone would be willing to answer a few basic questions I have? Of course I am using the relevant help guides... Thanks, Brian Quinif ps. If there is anyone at UGA on this list, I'd love to hear from someone local.

When I try to install hte Econometrics view I get the following error: CRAN task view Econometrics not available in: install.views("Econometrics") I have already install the ctv package and loaded it before trying to install the above... Any ideas as to what's going on?

Dear R users, A co-worker and I are writing a function to facilitate graph plotting in R. The function makes use of a lot of lists in its defaults. However, we discovered that R does not necessarily preserve the defaults if we were to input them in the form of list() when initializing the function. For example, if you feed the function codes below into R: myfunction=function( list1=list

Dear R users, I am using the Match function to generate nearest neighbor matching estimators. On that front I am ok, but where I am having problems is getting my output into nice LaTeX tables. Here is some basic code imitating the estimation I'm doing. No problem there. library(Matching) #make up some data X1 <- matrix(rnorm(1000*5), ncol=5) Y1 <- as.vector(rnorm(1000)) Tr1 <-

Consider this: > y <- matrix(1:8, ncol=2) > is.matrix(y[-c(1,2),]) [1] TRUE > is.matrix(y[-c(1,2,3),]) [1] FALSE > is.matrix(y[-c(1,2,3,4),]) [1] TRUE It seems like an inconsistent behaviour: - with 2 or more rows we have a matrix - with 1 row we do not have a matrix and - with 0 rows we have a matrix again I just stumbled on this behaviour, because I had a problem with my

I am attempting to replicate some of my experience from SAS in R and assume there are best methods for using a combination of summary(), subset, and which() to produce a subset of mean values by categorical or ordinal factors. within sas I would write proc means mean data=dataset; class factor1 factor2 var variable1 variable2; RUN; producing an output with means for each variable by factor

I am graphing longitudinal data from three time points. I'd like to draw a solid line from point 1 to point 2, and then a dashed line from point 2 to point 3. It works if I do it in two steps: > first.vector <- c(mean(year1$variable1), mean(year2$variable1)) > second.vector <- c(NA, mean(year2$variable1), mean(year3$variable1)) > plot(first.vector, type="b",

Hello, I'm using SPSS at work but really would like to switch to R. Right now I'm trying to learn R in reproducing calculations I did with SPSS but am stuck with something that is quite simple and comprehensible in SPSS-Syntax: IF (variable1.fac = 0 AND variable2.num = 0) variable3=1. IF (variable1.fac = 0 AND variable2.num >= 1) variable3=2. IF (variable1.fac = 1 AND variable2.num =

Dear list, I am trying to use lme to build the analogue of the following SAS MIXED random specification: random int+Variable1+Variable2 /subject = Subject group=Condition type=vc; which gives a Condition-blocked heterogeneity in the random effects variance-covariance matrix. Needless to say, I have a hard time in specifying Condition-specific heterogeneities in the variance-covariance

Hi, I have a dataset in which there are in all 250 variables and for each variable the data is entered over the months. I need to calculate the percentage of missing values for each variable over each month and then plot a graph for that. I am running the following code for doing the same *ds <- read.csv(file="filepath", header=TRUE) attach(ds) may <-

I have a question about how to reference variables in a dataframe. Normally, after I have read in some Stata data using the following command all <- read.dta('all.dta') Whenever I want to use the variable "sat.vr1" in the "all" data frame, I do so using all$sat.vr1 However, I'd like to be able to use the sat.vr1 variable without the "all$" (as well

Hi there, I have a huge dataframe containing 70,000 observations. I have filtered this dataframe (let it's name be "transformed_dataframe") as I wanted to select only those observations which are greater than or equal to 60,001 regarding the very first identity column. So I have a transformed dataframe now including 10,000 obeservations (from 60,001 - to 70,000) and if you send

Hi guys I seem to be having a problem, I don't know if it's a bug or whether I'm just doing it incorrectly. I want to set about 3 channel variables when I originate a call via AMI. All the documentation I have found says to do it like this: Variable: variable1=value|variable2=value|variable3=value However when I do this it runs them all together and I end up with:

Hello, I have many hundred variables in my longitudinal dataset and lots of missings. In order to plot data I need to remove missings. If I do > data <- na.omit(data) that will reduce my dataset to 2% of its original size ;) So I only need to listwise delete missings on 3 variables (the ones I am plotting). data$variable1 <-na.omit(data$variable1) does not work. Thank you

Dear list, I have a set of 100+ variables. I would like to have one by one crosstables for each variable. I started with table(variable1, variable2) table(variable1, variable3) table(variable1, variable4) ... table(variable2, variable3) table(variable2, variable4) ... It seems rather tedious. Any better ideas around? Thanks for any help! Gerit -- NUR NOCH BIS 31.01.! GMX FreeDSL -

Hi R people Pulling my hair out here trying to get something very simple to work. Have a data frame of 774 rows and want to plot first and second half on same axes with different colours. A variable is present call 'row' created like this and checked to be OK: row <- seq( len=length( variable1 ) ) ...so I just want to plot the two subsets where row <= 387 and where row