To elaborate on what Bert said: Lists are a variable length data structure which can hold most anything (even other lists) in them and are a great way to organize the sort of data you're working with. You can think of them as "generic vectors." You can assign them names and access/subset them by names or by element number. Perhaps most usefully, instead of passing all the vectors to a function which may need them, you can simply pass the one list object. This will make things much easier to maintain in the long run/
Most everything complicated in R like data.frames or model objects are internally implemented as lists (with various added features) and they [lists] are exceptionally powerful. It will seem like more overhead now than the lots-of-simple-vectors approach, but in the long run, it will be most certainly worth it. Best, Michael On Sun, Jun 24, 2012 at 4:30 PM, Bert Gunter <gunter.ber...@gene.com> wrote: > Standard response: Use lists instead. > > Read An Intro to R to learn about lists. In fact,read an An Intro to R, > full stop ( if you have not already done so). > > Cheers, > Bert > > On Sun, Jun 24, 2012 at 2:15 PM, Taylor White > <taylorgentrywh...@gmail.com>wrote: > >> Good day, >> >> For lack of a better solution (or perhaps I am ignorant to something >> more elegant), I have been bootstrapping panel data by hand so to >> speak and I would like to know if there is a way to define multiple >> variables in a loop using the loop variable. I found a post (here: >> https://stat.ethz.ch/pipermail/r-help/2002-October/026305.html ) that >> discussed naming multiple variables but it didn't seem to allow me to >> define the variables as something more useful. I tried the code >> immediately below (plus some variations) and it just didn't work. >> >> for (i in 1:20) { >> assign(paste("country.", i, sep = "") <- subset(OECDFiscal2, Country == i) >> } >> >> >> I included some sample code from what I've been working on below so >> one can see how it would be very useful to figure out how to define a >> series of variables from cross sectional units from a panel dataset. >> >> >> Any help would be much appreciated. >> >> >> Thanks, >> >> Taylor White >> UCLA >> >> >> >> ######Bootstrapping panel data by hand. Create 4 variables from 3 >> subsets of the original data. Resample each variable and recombine >> into one matrix. >> >> >> plmcoef <- array(0, c(1000, 4)) #creates an empty array to store >> regression coefficients >> plmfixef <- array(0, c(1000, 3)) #creates an empty array to store >> fixed effects intercepts from regressions >> >> >> for (i in 1:1000) { >> country1 <- as.data.frame(subset(OECDFiscal2, Country == 1)) >> country2 <- as.data.frame(subset(OECDFiscal2, Country == 2)) >> country3 <- as.data.frame(subset(OECDFiscal2, Country == 3)) >> >> exp1 <- as.matrix(sample(country1$lagexpVSgdp, size = >> (nrow(country1)), replace = T)) >> exp2 <- as.matrix(sample(country2$lagexpVSgdp, size = >> (nrow(country2)), replace = T)) >> exp3 <- as.matrix(sample(country3$lagexpVSgdp, size = >> (nrow(country3)), replace = T)) >> >> tax1 <- as.matrix(sample(country1$lagtaxVSgdp1, size = >> (nrow(country1)), replace = T)) >> tax2 <- as.matrix(sample(country2$lagtaxVSgdp1, size = >> (nrow(country2)), replace = T)) >> tax3 <- as.matrix(sample(country3$lagtaxVSgdp1, size = >> (nrow(country3)), replace = T)) >> >> gdp1 <- as.matrix(sample(country1$yoygdpcapita, size = >> (nrow(country1)), replace = T)) >> gdp2 <- as.matrix(sample(country2$yoygdpcapita, size = >> (nrow(country2)), replace = T)) >> gdp3 <- as.matrix(sample(country3$yoygdpcapita, size = >> (nrow(country3)), replace = T)) >> >> unemployment1 <- as.matrix(sample(country1$lagunemployment, size = >> (nrow(country1)), replace = T)) >> unemployment2 <- as.matrix(sample(country2$lagunemployment, size = >> (nrow(country2)), replace = T)) >> unemployment3 <- as.matrix(sample(country3$lagunemployment, size = >> (nrow(country3)), replace = T)) >> >> country.year1 <- as.matrix(cbind(country1$Country, country1$Year2)) >> country.year2 <- as.matrix(cbind(country2$Country, country2$Year2)) >> country.year3 <- as.matrix(cbind(country3$Country, country3$Year2)) >> >> country1.2 <- as.data.frame(cbind(country.year1, exp1, tax1, gdp1, >> unemployment1)) >> country2.2 <- as.data.frame(cbind(country.year2, exp2, tax2, gdp2, >> unemployment2)) >> country3.2 <- as.data.frame(cbind(country.year3, exp3, tax3, gdp3, >> unemployment3)) >> >> data <- as.data.frame(rbind(country1.2, country2.2, country3.2)) >> >> OECDsamplepanel <- pdata.frame(data, index = NULL, drop = F) >> >> plm <- plm(V5 ~ lag(V6, 1) + V3 + V4 + V5, data = OECDSamplepanel, >> model = "within") >> >> coefficients <- t(as.matrix(plm$coefficients)) >> fixef <- t(as.matrix(fixef(plm))) >> >> plmcoef[i, 1:4] = coefficients >> plmfixef[i, 1:3] = fixef >> >> } >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > > > -- > > Bert Gunter > Genentech Nonclinical Biostatistics > > Internal Contact Info: > Phone: 467-7374 > Website: > http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
