similar to: "Types" of missingness

Dear R-Listers, My question concerns indexing vectors by logical vectors that are based on the original vector. Consider the following simple example to hopefully make clear what I mean: a <- rnorm(10) a[a<0] <- NA However, I am now working with multiple data frames that I received, where each of them has nicely descriptive, yet long names(). In my scripts there are many instances

Dear R users, I am looking for more efficient way to compute the followings -------------------------------------------------------------------------- a <- matrix(c(1,1,1,1,2,2,2,2),4,2) b <- matrix(c(1,2,3,4),4,1) Eventually, I want to get this matrix, `c`. c <- matrix(c(1/1,1/2,1/3,1/4,2/1,2/2,2/3,2/4),4,2) --------------------------------------------------------------------------

Dear list, I have two vectors: x <- c("one","two") y <- paste(rep(x,2),"blah") I want to replace all occurrences of each element of x in y with something else, so that y looks like this: y [1] "something else blah" "something else blah" "something else blah" [4] "something else blah" I can do this using a loop: for (

Hello R-listers, I am using xtable to create some LaTeX tables for me to Sweave into my document. I am now trying to set the number of digits that will be reported in several _rows_ in my table. The 'digits' option in xtable() sets the number of digits to display for specified columns. Am I missing another obvious option to do the same thing for rows? A quick RSiteSearch didn't turn

Hi, I am new to R. My problem is with the ordered logistic model. Here is my question: Generate an order discrete variable using the variable wrwage1 = wages in first full calendar quarter after benefit application in the following way: * wage*1*Ordered *= 1 *if*0 *· wrwage*1 *< *1000 2 *if*1000 *· wrwage*1 *< *2000 3 *if*2000 *· wrwage*1 *< *3000 4 *if*3000 *· wrwage*1 *<

Hello all, I upgraded my R workstation, and to my dismay, only one core appears to be used during intensive computation of a bioconductor function. What I have now is two dual-core Xeon 5160 CPUs and 10 GB RAM. When I fully load it, top reports about 25% user, 75% idle and 0.98 short-term load. The archives gave nothing helpful besides mention of snow. I thought of posting to HPC, but this system

Suppose we observe N individuals, for each of which we have a time-series. How do we correctly create a lagged value of the time-series variable? As an example, suppose I create: A <- data.frame(year=rep(c(1980:1984),3), person= factor(sort(rep(1:3,5))), wage=c(rnorm(15))) > A year person wage 1 1980 1 0.17923212 2 1981

Hello, As you can see from my signature in this message, I use the R fortune function to generate a fortune, which is then fed to the signature program, which constructs a named pipe containing the fortune-bearing sig, which is then included in mail messages. The problem is that it's got extraneous junk in it and I can't figure out how to get rid of it. This is the command that generates

I'm trying to read two data sets in json format from a single .js file. I've tried fromJSON() in both RJSONIOIO and RJSON packages, but they require that the lines be pre-parsed somehow in ways I don't understand. Can someone help? > wheat <- readLines("http://mbostock.github.com/protovis/ex/wheat.js") > str(wheat) chr [1:70] "var wheat = [" "

Dear all, I have 1980~1990 eleven datas, every year have three variables, wage gender(1=female, 2=male) race(1=black, 2=white) My original commands is: fig2b<-reldist(y=mu1990$wage,yo=mu1980$wage,.......) I have three questions: 1. If I want to appoint y=women's wage in 1990 yo=women's wage in 1980 2. If I want to appoint y=women's wage in

Hello, Hierarchical factors are a very common data structure. For instance, one might have municipalities within states within countries within continents. Other examples include occupational codes, biological species, software types (R within statistical software within analytical software), etc. Such data structures commonly use hierarchical coding systems. For example, the 2007 North

I am trying to simulate the trajectory of the pension assets of one person. In C-like syntax, it looks like this: daily.wage.growth = 1.001 # deterministic contribution.rate = 0.08 # deterministic 8% Wage = 10 # initial Asset = 0 # initial for (10,000 days) { Asset += contribution.rate * Wage

Hello list, I'm following the paper (http://www.jstatsoft.org/v27/i02/paper) on how to use "plm" to run panel regressions, and am having trouble with what I believe should be something very basic. When I run the command (p.9 in the paper): R> dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) I see: emp ~ wage +

Hello, I am fairly new with R and am having trouble finding an optimal group. I checked the help functions for the various optimize commands and it was a little over my head. I have a dataset with 4 columns, name, type, value, and cost. The set consists of a list of people, which have 3 types. I want to choose 6 people, two of each type, and maximize the sum of their values. However, I'm

Dear John Fox, Christian Kleiber, and Achim Zeileis, I am attempting to run various independent variable parameters to assess their suitability. Unfortunately, I hit a snag and couldn't get the tests to run properly. When I used ivreg, I got an error message saying: "Error in eval(predvars, data, env) : object 'WageInequality' not found." Can you please help? Model:

Hi, I'm trying to do a regression like this: wage.r = lm( log(WAGE) ~ log(EXPER) where EXPER is an integer that goes from 0 to about 50. EXPER contains some zeros, so you can't take its log, and the above regression therefore fails. I would like to make R accept log(0) as 0, is that possible? Or do I have first have to turn the 0's into 1's to be able to do the above

Hello, I have a set of data including age, wage and education level each called age76, wage76 and grade76 I want to know how i can calculate the average wage of people age 15 to 65 (each year separetly) , only for those who have an education level of 10 12 and 16... -- View this message in context: http://r.789695.n4.nabble.com/Conditional-average-tp4585313p4585313.html Sent from the R help

Hello, I am switching to R from Stata and I am having particular trouble with the transition from Stata's 'xtabond' and 'ivreg' commands to the "plm" package. I am trying to replicate some of the dynamic panel data work using the UK Employment data in Arellano and Bond (1991) and available as 'EmplUK' under the 'plm' package. I have been

Dear friends, I am trying to understand and implement instrumental variables regression using R. I found a small (simple) example here which purportedly illustrates the mechanics (using 2-stage least-squares): http://www.r-bloggers.com/a-simple-instrumental-variables-problem/ Basically, here are the R commands (reproducible example) from that site: # ------ begin R library(AER)

Hi its me again I don't mean to get on your nerves, but the use of R proofs to be a bit more complicated than envisaged. I would like to calculate the mean of a group of values, here "wage_accepted". The group is determined by the stage and period, so in the end there should be a column with the values of the wages in period 1 stage1, period 1 stage 2, period 2 stage1...