search for: precincts

FWIW, here's a little data set I collected yesterday while working as an election judge in a precinct in Maryland: End DEM REP IND LIB OTH 8:00 40 12 7 1 0 9:00 30 7 3 0 0 10:00 35 13 6 0 0 11:00 31 10 8 0 0 12:00 23 4 2 0 0 1:00 23 5 0 0 0 2:00 20 8 1 0 0 3:00 24 5 6 0 0 4:00 15 6 4

Dear all, in GADM map there are three levels (nation, province and precinct) for each country of the world but for all of them you are never able to plot only one part of a chosen country. To be sure, I am trying to plot only one region of “Italy” and colour the different precincts in it. So far I am able to colour only the part of my interest but the programme still plot the whole country. Is that a way to have only a chosen part of the country (ie. region or state) with all the specific subunits in it? I have tried also to plot and then zoom but the “zoom” function seems...

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have the following data: > y [1] 0.000 0.004 0.008 0.016 0.024 0.032 0.044 0.064 0.072 0.088 0.108 0.140 [13] 0.156 0.180 0.208 0.236 0.264 0.296 0.320 0.360 0.408 0.444 0.472 0.524 [25] 0.576 > x [1] 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 [16] 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 I'd

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm generating a symmetric correlation matrix using a data matrix as input: mat <- cor(data.mat) My question is: Is there a more memory efficient way to store this data? For instance, since: all(mat == t(mat)) every value is duplicated, and I should be able to almost half the memory usage for large matrices. Any thoughts/comments? Cheers,

Are there any particular licences under which R packages must be released or is it the discretion of the author? The same question if the package is to be destined for CRAN? Kind regards, Nathan -- -------------------------------------------------------- Dr. Nathan S. Watson-Haigh OCE Post Doctoral Fellow CSIRO Livestock Industries Queensland Bioscience Precinct St Lucia, QLD 4067 Australia

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have a rectangular matrix of size 920 by 85. I'd like to coerce it into a square matrix such that all row/col names are present in the new matrix and the additional values are zero. As an example: A B C D A 1 2 3 4 E 5 6 7 8 F 9 10 11 12 Would be coerced to: A B C D E F A 1 2 3 4 5 9 B 2 0 0 0 6 10 C 3 0 0

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm trying to add some Fortran 90 code to an existing package. When I compile and load the file manually like: SHELL> R CMD SHLIB file.f90 R> dyn.load("file.so") I can use the .Fortran() fine. However, when I try to build, install and load the library I seem to be missing something. I do a: SHELL> R CMD build dir SHELL> R

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I've written a function in R which takes a symmetrical matrix as input and processes all triplicate combinations of values from the matrix. The function looks something like: my_fun <- function(m) { if( nrow(mat) != ncol(mat) ) { stop("'m' must be a square matrix") } size <- nrow(m) for(x in 1:(size -2)) {

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'd like to be able to colour histograms along the diagonal using the colours stored in colnames(d): > d black blue brown cyan 1 0.96405751 -0.02964390 -0.060147424 -0.06460070 2 -0.03614607 0.95475444 -0.152382053 -0.07767974 3 -0.07095613 -0.05884884 -0.061289399 -0.06445973 4 -0.03708223 -0.05997624

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I was wondering if anyone could point me in the right direction for reading up on writing tests in R. I'm writing some functions for inclusion into a package and would like to test them to ensure they're doing what I expect them to do. Are these approaches used for testing packages in CRAN? Cheers, Nathan - -- -

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm trying to calculate Pearson correlation coefficients for a large matrix of size 18563 x 18563. The following function takes about XX minutes to complete, and I'd like to do this calculation about 15 times and so speed is some what of an issue. Does anyone have any suggestions on ways to speed this up? I'd wondered if using C++ code to

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have some data generated as follows: <code> n <- 2000 work <- vector() for(x in 1:n) { work[x] <- sum(1:(n-x+1)) } plot(work) </code> What I want to do - ----------------- I want to split work into a number of unequal chunks such that the sum of the values in each chunk is approximately equal. The numbers in

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm trying to understand some C code in an R package I'm using. I'm address this question here as it's matrix algebra...and I'm no pro at that! the C command reads: double alpha = 1.0, beta = 0.0; dsyrk_("L", "N", nGenes, nGenes, & alpha, mat1, nGenes, & beta, mat2, nGenes); - From google,

When you try to upgrade on a test stand, an error occurs. I do not understand that you need to add ldap, or improve migration script? Before that I tried to version 4.1.7, but the error was the sam root at dc1:~/smb_old# samba --version Version 4.2.2-SerNet-Ubuntu-7.trusty I also modified the file --- ./upgrade.py 2014-10-01 00:00:00.000000000 +0600 +++

Hi I apologise for this question as it really must be a FAQ. Unfortunately, I can't find the answer and I'm tired of looking at endless google results A colleague of mine works for a state government department that has a policy against open source software or software tainted by open source. Other government departments in the same state use R but this particular department is driven

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Is there a library which is capable of identifying distinct clusters of size n from a series of XY coordinates? Failing this, I'd like to be able to to something like: Using a sliding window of size n along the x-axis I'd like to determine the distance between the center of the points in the window and the closest point outside the window. I

A new release of the conf.design package has been submitted to CRAN. This is largely a "tidying up" release, with no substantial change in functionality. The one difference some users may notice is that the method functions factorize.default factorize.factor are no longer exported directly, but instead are simply registered as S3 methods in the namespace. This change should not

I have submitted a tiny new package to CRAN, lazyData. This has a single function requireData which is designed as a drop-in replacement for base::require. In addition to doing the same job as base::require, it supplies a LazyData facility for those packages which have data but do not provide LazyData. The call is the same as for base::require but with an additional side-effects. After the

A new release of the conf.design package has been submitted to CRAN. This is largely a "tidying up" release, with no substantial change in functionality. The one difference some users may notice is that the method functions factorize.default factorize.factor are no longer exported directly, but instead are simply registered as S3 methods in the namespace. This change should not

I have submitted a tiny new package to CRAN, lazyData. This has a single function requireData which is designed as a drop-in replacement for base::require. In addition to doing the same job as base::require, it supplies a LazyData facility for those packages which have data but do not provide LazyData. The call is the same as for base::require but with an additional side-effects. After the