similar to: eval a SYMSXP from C

I need to refresh my memory on Probability Theory, especially on conditional probability. In particular, I want to solve the following two problems. Can somebody point me some good books on Probability Theory? Thank you! 1. Z=X+Y, where X and Y are independent random variables and their distributions are known. Now, I want to compute E(X | Z = z). 2.Suppose that I have $I \times J$ random number

Dear all this is a question of model specification in lme which I'd for which I'd greatly appreciate some guidance. Suppose I have data in long format gene treatment rep Y 1 1 1 4.32 1 1 2 4.67 1 1 3 5.09 . . . . . . . . . . . . 1 4 1 3.67 1 4 2 4.64 1 4 3 4.87 .

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hello, I have a simple question on the text() method in plots, e.g.: text(3,4,adj=1,cex=1.0, expression(alpha == beta)) I know there exists a lot more like frac(), etc which could be used for expression. But a help(frac) doesn't return any results - where do I have to look for a documentation of possible text commands? More in detail I'm

Hi, Again, sorry for the length of this post. Once I get my new office I will get a website set up on my work machine and will simply post a link to the log since I doubt many people are truly interested in these logs. To further analyze what is happening, I added my own routine in main.c called DEBUG_SET_NAMED and then redefined the SET_NAMED macro to use it and then rebuilt R. I

Dear R Help, I am trying to fit a nonlinear model for a mean function $\mu(Data_i, \beta)$ for a fixed covariance matrix where $\beta$ and $\mu$ are low- dimensional. More specifically, for fixed variance-covariance matrices $\Sigma_{z=0}$ and $\Sigma_{z=1}$ (according to a binary covariate $Z $), I am trying to minimize: $\sum_{i=1^n} (Y_i-\mu_(Data_i,\beta))' \Sigma_{z=z_i}^{-1} (Y_i-

Hello, I?m experimenting with ALTREP and was wondering if there is a preferred way to create an ALTREP wrapper vector without using .Internal(wrap_meta(?)), which R CMD check doesn?t like since it uses an .Internal() function. I was trying to create a factor that used an ALTREP integer, but attempting to set the class and levels attributes always ended up duplicating and materializing the

Hi Group, Here is some data. p <- runif(1000) # sample data groups <- rep(c(1,2),each=500) #conditioning variable mydata <- cbind(p,groups) n <- length(p) u <- (1:n)/(n + 1) # uniform distribution reference for qqplot logp <- -log(p,base=10) logu <- -log(u,base=10) qqplot(logp,logu) How can I make the above qqplot in lattice and/or ggplot2. The sample is uniform, and I take

Hi, I expected NAMED to be 1 in all these three cases. It is for one of them, but not the other two? > R --vanilla R version 2.14.0 (2011-10-31) Platform: i386-pc-mingw32/i386 (32-bit) > x = 1L > .Internal(inspect(x)) # why NAM(2)? expected NAM(1) @2514aa0 13 INTSXP g0c1 [NAM(2)] (len=1, tl=0) 1 > y = 1:10 > .Internal(inspect(y)) # NAM(1) as expected but why different to x?

There seems to be a latent flaw in the definition of struct SEXPREC in Rinternals.h, which likely doesn't cause problems now, but could if the relative sizes of data types changes. The SEXPREC structure contains a union that includes a primsxp, symsxp, etc, but not a vecsxp. However, in allocVector in memory.c, zero-length vectors are allocated using allocSExpNonCons, which appears to

Hi Jiefei and Kylie, Great to see people engaging with the ALTREP framework and identifying places we may need more tooling. Comments inline. On Thu, Jul 18, 2019 at 12:22 PM King Jiefei <szwjf08 at gmail.com> wrote: > > If that is the case and you are 100% sure the reference number should be 1 > for your variable *y*, my solution is to call *SET_NAMED *in C++ to reset > the

Full_Name: Ed Borasky Version: 1.8.1 OS: Windows XP Professional Submission from: (NULL) (208.252.96.195) R 1.8.1 seems to be running into a memory allocation problem in the "aggregate" function. I have a rather large dataset (14 columns by 223,000 rows -- almost 40 megabytes) and a script that performs some processing on it. The system is a 768 MB Pentium 4. Here's the console

[some de-capitalization of *SXP done manually by mailing list maintainer ; the originally was caught as potential spam. MM] I have a little R program that crashes with the message xmalloc: out of virtual memory The code has a repeat{} loop that watches the sizes of some files. When there's an increase it updates things by reading the last 65 lines of each file, doing some

I'm trying to track down a bug in some experimental code, where an object's attribute is getting messed up. This means I'd like to examine R objects while within gdb. One of the things I'd like to do is to examine the names of all the attributes. This is exactly what an example in the R Extensions manual section 4.11.2 "Inspecting R objects when debugging" does,

Dear R users, I am trying to find a package that can estimate an autoregressive model for discrete data. I am imagining a Poisson or Gamma process in which the mean (say mu) follows a process such as mu_t = a + b*x + c*mu_{t-1} Suppose I have data on the time-series Poisson outcomes and x and would like to obtain ML estimates for b and c. Does anyone know of a package that can do this

On Thu, Jan 8, 2015 at 11:57 AM, <luke-tierney at uiowa.edu> wrote: > On Thu, 8 Jan 2015, Michael Lawrence wrote: > > If we do add an argument to get(), then it should be named consistently >> with the ifnotfound argument of mget(). As mentioned, the possibility of a >> NULL value is problematic. One solution is a sentinel value that indicates >> an unbound value

Hello, (This is follow up from this thread: http://www.nabble.com/execution-time-of-.packages-td22304833.html but with a different focus) I am often confused by the result of the profiler, when a loop is involved. Consider these two scripts: script1: Rprof( ) x <- numeric( ) for( i in 1:10000){ x <- c( x, rnorm(10) ) } Rprof( NULL ) print( summaryRprof( ) ) script2:

Given a vector : pvec=(p1,p2,.... p J) with sum(pvec)=1, all the elements are non-negative, that is, they are probabilities a matrix A ( N* J ), with the elements alpha(ij) are 0 or 1 I want to MAXIMIZE THE RESULT RESULT= product( i=1, to N [ sum ( alpha(ij)* pj , j =1,to J ) ] ) thus, I need to get pvec. how should I do ? for example

[Re-directing to R-devel, as I think this needs changes to the code.] Can I suggest a modification to stats:predict.princomp so that it will check for column (variable) names? In src/library/stats/R/princomp-add.R, insert the following after line 4: if (!is.null(cn <- names(object$center))) newdata <- newdata[, cn] Now Dana's example looks like: > predict(pca1, frz) Error in

On Tue, Jan 11, 2011 at 2:41 PM, Romain Francois <romain@r-enthusiasts.com>wrote: > Le 11/01/11 19:57, Romain Francois a écrit : > > Le 11/01/11 19:46, Douglas Bates a écrit : >> >>> On Tue, Jan 11, 2011 at 12:27 PM, Dominick >>> Samperi<djsamperi@gmail.com> wrote: >>> >>>> >>>> >>>> On Tue, Jan 11, 2011 at

Hi, everyone. I'm trying to debug an R-module, written in C, and I'm using gdb for this. How can I print "standard" R objects from within C code? BTW, I'm familiar with the advice to use R_PV given in Writing R Extensions, but it's not working for me. E.g., I get (gdb) p R_PV(x) $1 = void and yet (gdb) p *x $2 = {sxpinfo = {type = 16, obj = 0, named = 0, gp = 0,