[R] Unexpected R Behavior: Adding 4 to Large Numbers/IDs Containing Current Year
Hello, I have encountered some unexpected behavior in R that seems to occur as a result of having the current year embedded in a number: #Some large numbers, representing IDs. IDs - c(41255689815201100, 41255699815201100, 41255709815201100) #In scientific notation IDs [1] 4.125569e+16 4.125570e+16 4.125571e+16 #Change penalty. options(scipen = 5) #Why does R add 4? IDs [1] 41255689815201104 41255699815201104 41255709815201104 #Changing from numeric to character makes no difference. as.character(IDs) [1] 41255689815201104 41255699815201104 41255709815201104 #What happens if I treat the numbers as characters? IDs.character - c(41255689815201100, 41255699815201100, 41255709815201100) #No change. IDs.character [1] 41255689815201100 41255699815201100 41255709815201100 #R adds 4 upon converting to numeric. as.numeric(IDs.character) [1] 41255689815201104 41255699815201104 41255709815201104 #Is this problem occurring because the current year is embedded in the number? IDs - c(41255689815201100, 41255699815201000, 41255709815201200) #R is no longer adding 4 to the numbers without 2011. IDs [1] 41255689815201104 41255699815201000 41255709815201200 Am I doing something wrong? Any insight on how I can avoid the problem of R changing numbers on its own? Are others able to replicate this example? Is this some kind of bug? Am I right that this problem is occurring because the current year is embedded in the number? I discovered this when trying to merge two data sets, one with IDs stored numbers and one with IDs as characters. I have replicated this in Windows XP with R 2.12 and Windows 7 with R 2.13 (both 32- and 64-bit versions). Thanks, Chris -- Christopher T. Moore, M.P.P. Doctoral Student Quantitative Methods in Education University of Minnesota 44.9785°N, 93.2396°W moor0...@umn.edu http://umn.edu/~moor0554 __ 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] Flexibly Retrieving Objects with an Index
Greetings, I would like to flexibly combine several data frames objects without specifying the exact names of the objects in memory. Should I use indexing to call those objects out of memory? I regularly use indexes to flexibly extract parts of data frames and lists and to read files from my hard drive, but I can't figure out how to do so with stored objects. In my case, all of the data frames of interest are formatted the same way and have been assigned to objects with the prefix data.. The following examples combine only the names (not the objects themselves): rbind(ls()[grep(data., ls(), fixed=T)]) list(ls()[grep(data., ls(), fixed=T)]) Is there a way to get ls() (or some other function) to return the object instead of just the name? I searched the help files and the R-help archives but couldn't find a solution. Thanks in advance. Sincerely, Chris -- Christopher T. Moore, M.P.P. Doctoral Student Quantitative Methods in Education University of Minnesota 44.9785°N, 93.2396°W moor0...@umn.edu http://umn.edu/~moor0554 __ 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.
Re: [R] Flexibly Retrieving Objects with an Index
That works great. Thanks, Henrique. -Chris -- Christopher T. Moore, M.P.P. Doctoral Student Quantitative Methods in Education University of Minnesota 44.9785°N, 93.2396°W moor0...@umn.edu http://umn.edu/~moor0554 On Feb 2 2011, Henrique Dallazuanna wrote: Try this: do.call(rbind, mget(ls(pattern = 'data'), envir = .GlobalEnv)) On Wed, Feb 2, 2011 at 5:20 PM, Christopher T. Moore moor0...@umn.eduwrote: Greetings, I would like to flexibly combine several data frames objects without specifying the exact names of the objects in memory. Should I use indexing to call those objects out of memory? I regularly use indexes to flexibly extract parts of data frames and lists and to read files from my hard drive, but I can't figure out how to do so with stored objects. In my case, all of the data frames of interest are formatted the same way and have been assigned to objects with the prefix data.. The following examples combine only the names (not the objects themselves): rbind(ls()[grep(data., ls(), fixed=T)]) list(ls()[grep(data., ls(), fixed=T)]) Is there a way to get ls() (or some other function) to return the object instead of just the name? I searched the help files and the R-help archives but couldn't find a solution. Thanks in advance. Sincerely, Chris -- Christopher T. Moore, M.P.P. Doctoral Student Quantitative Methods in Education University of Minnesota 44.9785°N, 93.2396°W moor0...@umn.edu http://umn.edu/~moor0554 http://umn.edu/%7Emoor0554 __ 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.
[R] Heterogeneous Correlation Matrix with Survey Weights
Hello, I have a data set containing categorical and ordinal factors, as well as sampling weights (i.e., survey weights reflecting unequal probabilities of selection). I want to fit a structural equation model with sem(). I have run sem() on weighted covariance matrices using advice from John Fox (see http://tolstoy.newcastle.edu.au/R/e5/help/08/12/8773.html and http://blog.lib.umn.edu/moor0554/canoemoore/2009/09/sem_complex_samples_r_update.html). However, since I have categorical/ordinal variables, I would like to compute a weighted heterogeneous correlation matrix with hetcor(). Is there a way to do this in R? I couldn't find any guidance in the r-help archives or in the polycor help files. Should I truncate the sampling weights to integers and then populate the data set with redundant rows/cases so that the number of rows equals the population size (N700,000)? Or is there a better way to compute a weighted heterogeneous correlation matrix? Thanks, Chris -- Christopher T. Moore, M.P.P. Doctoral Student Quantitative Methods in Education University of Minnesota 44.9785°N, 93.2396°W moor0...@umn.edu http://umn.edu/~moor0554 __ 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] Error from termplot() with make.panel.svysmooth() for complex survey data
Greetings,
I am using library(survey) to analyze some complex sample data. After
fitting a model I tried to use termplot() with make.panel.svysmooth(), but
I received an error (see below).
Could someone help me interpret the error message so I can make the
necessary corrections? The make.panel.svysmooth() function seems to work
fine, and termplot() worked fine after I dropped the smoother. This led me
to believe that the error is coming from panel.smooth(), but the code for
that function does not contain the rowsum() and findInterval() functions
shown in the error message. I should also note that error does not depend
on the inclusion or omission of missing data, as I tried it both ways.
I'm analyzing private data, so I can't provide a reproducible example, but
here's the output:
design - svydesign(ids=~PSU, weights=~W,
strat=~STR, nest=T, data=data) model - svyglm(fmla, design=design)
#works fine as evidenced by summary (not shown) termplot(model,
data=model.frame(design), partial.resid=T, se=T,
smooth=make.panel.svysmooth(design))
Waiting to confirm page change... Error in rowsum.default(c(rep(0, ngrid),
w), c(1:ngrid, findInterval(mm[, :
incorrect length for 'group'
make.panel.svysmooth(design)
function (x, y, span = 2/3, col.smooth = red, col = par(col),
bg = NA, pch = par(pch), cex = 1, ...)
{
if (is.null(bandwidth))
bandwidth - range(x) * span/3
s - svysmooth(y ~ x, design = design, bandwidth = bandwidth)
points(x, y, pch = pch, bg = bg, col = col)
lines(s[[1]], col = col.smooth, ...)
}
environment: 0x0225a5d4
termplot(model, data=model.frame(design), partial.resid=T, se=T) #works
but without smoothing panel.smooth
function (x, y, col = par(col), bg = NA, pch = par(pch),
cex = 1, col.smooth = red, span = 2/3, iter = 3, ...)
{
points(x, y, pch = pch, col = col, bg = bg, cex = cex)
ok - is.finite(x) is.finite(y)
if (any(ok))
lines(stats::lowess(x[ok], y[ok], f = span, iter = iter),
col = col.smooth, ...)
}
environment: namespace:graphics
sessionInfo()
R version 2.9.2 (2009-08-24) i386-pc-mingw32 attached base packages: [1]
splines stats graphics grDevices utils datasets methods base other attached
packages: [1] quantreg_4.38 SparseM_0.80 KernSmooth_2.23-3 survey_3.16
car_1.2-15 foreign_0.8-37
Thanks in advance for any help you can provide.
Regards,
Chris
--
Christopher Moore, M.P.P.
Doctoral Student
Quantitative Methods in Education
University of Minnesota
44.9785°N, 93.2396°W
moor0...@umn.edu
http://umn.edu/~moor0554
__
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.
