[R] Defining multiple variables in a loop

[R. Michael Weylandt]

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.berton at 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
> <taylorgentrywhite at 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
>>
>> }
>>
>> ______________________________________________
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>> 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 at r-project.org mailing list
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> and provide commented, minimal, self-contained, reproducible code.