similar to: Where is opt spending its time?

Hi, I am very new to R and I've been trying to work through the R book to gain a better idea of the code (which is also completely new to me). Initially I imputed my data from a text file and that seemed to work ok, but I'm trying to examine linear relationships between gdist and gair, gdist and gsub, m6dist and m6air, etc. This didn't work and I think it might have something to do

Hi How would I analyse time series with - different lengths (i.e. one has 9 entries and the other has 14 entries) - different frequency (i.e. dates are random - no repeated length) - multiple values for the same time entry (e.g. 2009-10-23 below) i.e. my data takes the form: 1st time series 2009-10-07 0.009378 2009-10-19 0.014790 2009-10-23 -0.005946 2009-10-23 0.009096 2009-11-08 0.004189

Hi all! I tried to perform Shapiro-Wilk test for my sample of 243 values. > Us [1] -10.4 -13.1 -12.2 38.1 -18.8 -13.3 -11.7 29.3 49.7 6.8 12.7 16.3 [13] 5.8 -0.7 -29.4 4.1 38.8 -1.4 8.8 15.6 32.9 -5.3 19.1 35.8 [25] 4.0 -1.5 0.6 -4.2 -10.0 -4.0 1.1 48.9 -21.0 -5.3 5.8 -10.8 [37] 21.9 8.2 -3.2 -3.9 -2.3 12.6 -4.7 -8.0 11.8 27.4 -9.5 -20.8 [49]

Now that autoconf is going away soon, I figured I'd try building using CMake. I checked out llvm, cfe and lldb from the SVN server, and followed the basic build instructions. cmake -DBUILD_SHARED_LIBS=OFF -DCMAKE_INSTALL_PREFIX=/tools/llvm/svn_head -DLLVM_TARGETS_TO_BUILD="X86;CppBackend" -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_ASSERTIONS=ON ../llvm Everything worked well, and in

Hi R users, I'm here trying to understand correlated residuals in nonlinear estimation. I'm reading/studying the book Bates, D. M. and D. G. Watts, (1988), /Nonlinear regression analysis and its applications/, Wiley, NY. pages 92-94, trying to reproduce the figures and to find out the code in R to perform the necessary calculations. I also consulted Pinheiro and Bates, but without

Dear statistician experts, Sorry if this is a trivial question, or the old same question (i don't know what is the efficient key word for this issue). In order to understand the calculation of parameter of logistic regression, I did an exercise through spreadsheet following the procedural example from a literature, or the available spreadsheet (with calculation formula). I ended up with

Thanks - I'll try this tonight. Assuming it works, should these variables be added to the docs at http://llvm.org/docs/CMake.html ? On Wed, Jan 13, 2016 at 10:26 PM, Andrew Wilkins <axwalk at gmail.com> wrote: > > > On Thu, 14 Jan 2016 at 11:02 David Jones via llvm-dev < > llvm-dev at lists.llvm.org> wrote: > >> Now that autoconf is going away soon, I

I'm upgrading my application to use LLVM 3.7.1 instead of 3.5.1. On one of my regression tests I am getting an assertion: /home2/djones/llvm-3.7.1.src/lib/IR/Metadata.cpp:490: void llvm::MDNode::resolve(): Assertion `isUniqued() && "Expected this to be uniqued"' failed. This occurs when finalizing debug info prior to code generation: #4 0x00007ffff4520455 in

I''ve got some new gems up for Camping r90. The only change is that multipart/form-data POSTs are now parsed in chunks from the stream. So file uploads are efficient. Traditional POSTs are still parsed in-memory, but I hope this will change before 1.5. _why

https://bugzilla.samba.org/show_bug.cgi?id=10233 Summary: rsync is spending a lot of time lstat64()'ing --exclude'd files Product: rsync Version: 3.1.0 Platform: All OS/Version: All Status: NEW Severity: normal Priority: P5 Component: core AssignedTo: wayned at samba.org

Hello all! I have a problem to extract values greater that for example 1820. I try this code: x[x[,1]>1820,]->x1 Please help me! Thank you! The data structure is: structure(c(2.576, 1.728, 3.434, 2.187, 1.928, 1.886, 1.2425, 1.23, 1.075, 1.1785, 1.186, 1.165, 1.732, 1.517, 1.4095, 1.074, 1.618, 1.677, 1.845, 1.594, 1.6655, 1.1605, 1.425, 1.099, 1.007, 1.1795, 1.3855, 1.4065, 1.138, 1.514,

hi all, I am trying to get lm_sensors to work. did the yum install lm_sensors service lm_sensors start sensor -s and it says no sensors found. did lsmod | grep it87 and it87 57061 0 hwmon_vid 35905 1 it87 hwmon 36553 1 it87 i2c_isa 39105 1 it87 i2c_core 56129 5 it87,i2c_isa,i2c_dev,i2c_ec,i2c_piix4 Seems like

Hi All, I'm trying to get lm_sensors to work on a Shuttle with an AMD K10. The version of lm_sensors in the main CentOS repo is 2.10.7, which is two years old now. Support for the K10 was added about a year ago. So, does anyone know if there are binaries available for more recent versions of lm_sensors? Also, if anyone has knowledge of the sensors layout for recent Shuttle AMD motherboards,

Dear all, I have a date frame like this: X Y Z 22 24 4.3 2.3 3.4 5.3 ..... .... 57.2 23.4 34 What my purpose is: to sort the data frame by either X, Y or Z. sample output is (sorted by X) : X Y Z 2.3 3.4 5.3 ..... ...... 22 24 4.3 ... 57.2 23.4 34 I have no idea how to use sort, order or rank functions. Please help me out. Thanks! Leaf

I''ve been trying to install a 2.6.37-12 kernel from kernel-ppa on one of my Ubuntu machines without success. It keeps giving errors like this: [ 9.115544] ata9: exception Emask 0x0 SAct 0xf SErr 0x0 action 0x10 frozen [ 9.115550] ata9.00: failed command: READ FPDMA QUEUED [ 9.115556] ata9.00: cmd 60/04:00: d4:82:85/00:00:1f:00:00/40 tag 0 ncq 2048 in [ 9.115557]

Hello all! I have a problem with R. I try to merge data like this: structure(c(2.1785, 1.868, 2.1855, 2.5175, 2.025, 2.435, 1.809, 1.628, 1.327, 1.3485, 1.4335, 2.052, 2.2465, 2.151, 1.7945, 1.79, 1.6055, 1.616, 1.633, 1.665, 2.002, 2.152, 1.736, 1.7985, 1.9155, 1.7135, 1.548, 1.568, 1.713, 2.079, 1.875, 2.12, 2.072, 1.906, 1.4645, 1.3025, 1.407, 1.5445, 1.437, 1.463, 1.5235, 1.609, 1.738, 1.478,

Dear list, I have the following text to parse (originating from readLines as some lines have unequal size), st = c("START text1 1 text2 2.3", "whatever intermediate text", "START text1 23.4 text2 3.1415") from which I'd like to extract the lines starting with "START", and group the subsequent fields in a data.frame in this format: text1 text2

I think it's easy problem but I can't find solution. I have a vector: vec <- c (23.4, 3.0, 14.7, 7.7) and I would like to add all values which are inside my vector to each other. as a result a want to get one value like sum all values from my vector- sth=(23.4 + 3.0 + 14.7 + 7.7) PS. I usually don't know how long is my vector in my function -- View this message in

I'm a great fan of read.table(), but this time the data had a lot of cruft. So I used readLines() and editted the char vector to eventually get something like this: " 23.4 1.5 4.2" " 19.1 2.2 4.1" and so on. To get that into a 3 col numeric table, I first just used: writeLines(data,"tempfile")

I am trying to debug a package to submit it to CRAN and am getting a bunch of error messages. Most of the errors are because of the Rd files which were automatically populated by the package.skeleton function. I find the section on documentation to be pretty confusion in the R Extensions manual. Any help on getting these errors fixed would be hugely appreciated. Thanks. --Markus * checking for