Please use split() instead of strsplit().  Apologies to all.  --JIV


On Sun, Jun 24, 2012 at 11:38 PM, Jorge I Velez <> wrote:

> Dear Taylor,
>
> You might also try
>
> with(OECDFiscal2, strsplit(OECDFical2, Country))
>
> HTH,
> Jorge.-
>
>
>
> On Sun, Jun 24, 2012 at 11:31 PM, Taylor White <> wrote:
>
>> Thank you gentlemen for pointing me in the right direction.
>>
>> This code worked nicely:
>>
>>
>> countries <- list()
>>
>> for (i in 1:20) {
>> countries[[i]] = as.matrix(subset(OECDFiscal2, Country == i))
>> }
>>
>> Take care,
>>
>> Taylor
>>
>> On Sun, Jun 24, 2012 at 3:01 PM, R. Michael Weylandt
>> <michael.weylandt@gmail.com> wrote:
>> > 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@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@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.
>>
>
>

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