similar to: Clarification: Expedite scalar f(x) evaluation over vectors

Dear R community, I am trying to code a fairly complex equation for optim(). My current approach is too slow for optim(). I have a function that takes a double integral (hopefully correctly) across two terms, e.g., doubleint <- function(c1,c2) {integrate(function(y) { sapply(y, function(y) { integrate(function(x) {a*(c1+x)+b*(c2+x)}, boundsx[1], boundsx[2])$value }) },

I have a server that runs stand-alone with an LDAP directory and a KDC . The linux machines have sssd to allow unified users etc. The clients are mostly MacOS and Windows machines that aren't part of an AD. This config has worked for 15 years, but after upgrading Debian and bringing in Samba Version 4.17.7-Debian it seems to be broken. I believe this is related to:

I am helping my wife do some statistical analysis. She is a biologist, and she has performed some measurements on various genotypes of mice. My background is in applied mathematics and engineering, and I have a fairly good statistics background, but I am by no means a PhD level expert in statistical methods. We have used the lmer package to fit various models for the various experiments that she

I have executed a Repeated Measures ANOVA with one DV (latency) and one within subject factor (acoustic condtion: 3 levels) by bootstrapping my sampling distribution of F from the empirical sample distribution. I chose to resample because the sample distribution deviates from normality a lot. The overall F is significant and now I wish to decompose this with contrasts to ask if latencies to

[Yes, this is related to a homework problem, but is not the problems itself.] In my mathematical statistics class, we've just learned about properties of estimators, and I can now solve manually problems like this: A sample of size n = 16 is drawn from a normal distribution where sigma = 10 but mu is unknown. If mu = 20, what is the probability that the estimator mu hat = Y bar will lie

Hi! I'm translating some code from Matlab to R and I found a problem. I need to translate Matlab's function 'lsqnonlin' (http://www-ccs.ucsd.edu/matlab/toolbox/optim/lsqnonlin.html) into R, and at the beginning I thought it would be the same as R's 'optim'. But then I looked at the definition of 'lsqnonlin' and I don't quite see how to make

Folks, I wonder if anything could be said about the distribution of a random variate x, where x = N(0,1)/N(0,1) Obviously x is pathological because it could be 0/0. If we exclude this point, so the set is {x/(0/0)}, does x have a well defined distribution? or does it exist a distribution that approximates x. (The case could be generalized of course to N(mu1, sigma1)/N(mu2, sigma2) and one

Hi, New to R, I don't find a way to plot the following data with image(): x is a N * M matrix y is a vector of length M z is a N*M matrix I wish to plot z as a greyscale image, but my x axis is different for every row of the z data. Here is a minimal example, > theta<-c(3:6) # N > y<-c(1:5) # M > > x<-theta%*%t(y)# N * M > z<-sin(x) # N * M > > image(z)

Dear All, Is there any package to do multi-objective optimization? For instance, consider the following problem: maximize f(x,y) in order to x and maximize g(x,y) in order to y, simultaneously, with x and y being the same both for f and g. Can R do it numerically? Thanks in advance, Paul

I am a SAS user currently evaluating R as a possible addition or even replacement for SAS. The difficulty I have come across straight away is R's apparent difficulty in handling relatively large data files. Whilst I would not expect it to handle datasets with millions of records, I still really need to be able to work with dataset with 100,000+ records and 100+ variables. Yet, when reading

Hello: I am using R mainly on windows XP, version 2.5. I?m a biologist, with a medium level statistics background. I have a problem stating a two-way factorial design where both factors are random. I?m using the lmer() function implemented in the Matrix package version 0.99. My design is as follows: Two species were randomly selected from a total of 4 species. This species are present

I have 316 files. Each file represents a patient's breathing track (respiratory signal recorded for a variable number of cycles). All files have the same are made up of a header followed by a variable number of records. Each record contains 7 comma separated fields. The patient ID is recorder in the header which is stripped off when reading the file into a R data.frame. Since I need to keep

Dear All, I know how to export graphics as pdf files and then how to include them in LaTeX documents. However, I do not know how to do in order to have the text of the graphics written with the font selected for the LaTeX document. Is that possible? Thanks in advance, Paul

I'm looking for a function in R similar to t.test() which was generously pointed out to me yesterday, but which can be used for normally distributed data. To recap yesterday: > x <- scan() 1: 62 52 68 23 34 45 27 42 83 56 40 12: Read 11 items > alpha<- .05 > t.test(x) One Sample t-test data: x t = 8.8696, df = 10, p-value = 4.717e-06 alternative hypothesis: true

Try as I might I can't seem to get LLVM to bulid using clang/clang++. No matter what I do it insists on using /usr/bin/cc and /usr/bin/c++ which are gcc. Am I missing something obvious? I vaguely remember some document describing a stage1 compiler built by your old toolchain and a stage2 compiler but I can't find the steps to do that any more. $ CC=/usr/local/bin/clang

Hi, Given i have this share : [j.snow] Path = /home/j.snow Share and ntfs permission : j.snow user Now I add another folder share inside the first one : [a.stark] Path = /home/j.snow/a.stark Share and ntfs permission : a.stark user /home/j.snow/a.stark has now parent inherit permission (j.snow) AND a.stark user a.stark can't access to her share ! if I add a.stark NTFS access to [j.snow]

or add acl_xattr:ignore system acl = yes to your share. more info man smb.conf .. Gr. Louis >-----Oorspronkelijk bericht----- >Van: J.Morillo at educationetformation.fr >[mailto:samba-bounces at lists.samba.org] Namens MORILLO Jordi >Verzonden: vrijdag 5 juni 2015 15:21 >Aan: samba at lists.samba.org >Onderwerp: Re: [Samba] [Bug or Limitation] Folder sharing

I'd like to fit linear models on very large datasets. My data frames are about 2000000 rows x 200 columns of doubles and I am using an 64 bit build of R. I've googled about this extensively and went over the "R Data Import/Export" guide. My primary issue is although my data represented in ascii form is 4Gb in size (therefore much smaller considered in binary), R consumes about

clang revision is good, but the kernel is probably too new. Evgenii can comment on that. On Sat, Sep 12, 2015 at 3:23 PM, Greg Stark <stark at mit.edu> wrote: > On Sat, Sep 12, 2015 at 11:22 PM, Greg Stark <stark at mit.edu> wrote: > > Checked out a few days ago. It looks like r246697. I suppose I could > > try updating and rebuilding. > > Sorry, svn log in the

Hm, that bug has been closed as resolved but I still see the problem: $ clang --version clang version 3.8.0 (trunk 250848) (llvm/trunk 250846) Target: x86_64-unknown-linux-gnu Thread model: posix InstalledDir: /usr/local/bin configure:4042: ./conftest FATAL: Code 0x5615faea43f0 is out of application range. Non-PIE build? FATAL: MemorySanitizer can not mmap the shadow memory. FATAL: Make sure to