similar to: Rv generation

Hi, When writing formulae in Rd files I use \leq to get a less-than-or-equal-to sign, as this is what the LaTeX references I consulted suggested. This works correctly for the PDF output (Rcmd Rd2dvi.sh --pdf), however when the Rd file is converted to text or html this command is converted to "<=q". A workaround is to use \le instead of \leq which works with my LaTeX distribution

I think there are some missing words in "R Internals"'s description of the P_ macro. It currently has "A macro as a wrapper for ngettext", which I think ought to be something like "The macro P_ may be used as a wrapper for ngettext". The following patch also makes the 2 alternate definitions of P_ have the same argument names, StringS and StringP. Expanding the

I know this has been dealt with before on this list, but the previous messages lacked detail, and I haven't figured it out yet. The model is: \x_{ij} = \mu + \alpha_i + \beta_j \alpha is a random effect (subjects), and \beta is a fixed effect (condition). I have a link function: p_{ij} = .5 + .5( 1 / (1 + exp{ -x_{ij} } ) ) Which is simply a logistic transformed to be between .5 and 1.

Hello, I'm trying to fit a special kind of proportional odds model from: Whitehead et al. (2001). Meta-analysis of ordinal outcome using individual patient data. Statistics in medicine 20: 2243-2260. (model 2) The data are as follows: library(nlme) library(geepack) library(Design) library(MASS) options(contrasts=c("contr.SAS","contr.poly")) counts <-

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 UseRs: I have simulated data from a zero-inflated Poisson model, and would like to use a package like zicounts to test my code of fitting the model. My question is: can I use zicounts directly with the following simulated data? Create a sample of n=1000 observations from a ZIP model with no intercept and a single covariate x_{i} which is N(0,1). The logit part is logit(p_{i})=x_{i}*beta

Hi all, I'm new with R (and S), and relatively new to statistics (I'm a computer scientist), so I ask sorry in advance if my question is silly. My problem is this: I have a (sample of a) discrete time stochastic process {X_t} and I want to estimate Pr{ X_t | X_{t-l_1}, X_{t-l_2}, ..., X_{t-l_k} } where l_1, l_2, ..., l_k are some fixed time lags. It will be enough for me to compute

Hello, I'm fairly new to R and I can't work out how to produce a double inequality like (LaTeX) $0 \leq x \leq 1$ in the legend of a graph. If I try > legend(50, 0.1, legend = c(expression(0 <= x <= 1), c(2 <= x <= 3)), pch = c(1,1), col = c(2, 3)) then I get an error message "unexpected '<=' in ...". I've checked the help files for plotmath and

Hi, This is most likely only a minor technicality, but I saw the following: On page 6 of the 'parallel' vignette (http://stat.ethz.ch/R-manual/R-devel/library/parallel/doc/parallel.pdf), the random-number generator "L'Ecuyer-CMRG" is said to have seed "(x_n, x_{n-1}, x_{n-2}, y_n, y_{n-1}, y_{n-2})". However, in L'Ecuyer et al. (2002), the seed is given with

Hi all, Thanks to all who offered advice on using F95 in R. Now I'm trying to compile a test package using gfortran, Linux 2.4.21 and R 2.1.0. I was able to successfully compile and use a test F95 routine by setting my environment variables as follows in bash: export PATH=~/bin/:$PATH export F77=gfortran export LD_LIBRARY_PATH=~/bin/irun/lib export GFORTRAN_STDIN_UNIT=-1 Now I'm

Ok, I think my first mail didn't get through so I'll try this again. Please disregard. I'm trying to use subscripts on plot text. The help files say this can be done and give several example. I'm trying to do: P_{2} (for example) and so I tried: text(5,2,expression(P_{2})) which doesn't work. There are no subscript examples. I recall someone telling me that latex-like

Hi all, I wanto to run a plot about the levels of a variable parting on an ols regression. The regression in done on the rate of return of the variable. Imagine R_{t}=a+b*R_{t-1} So If P, the "estimated" price would be P_{t}=P_{t-1}*R_{t} Imagine that I obtain lm fitted values and the original R_{t}, R_{t-1} are [1000,1] dimmension... How it is posible to obtain also 1000,1 fitted

Hi all I recently started to write a matrix exponentiation operator for R (by adding a new operator definition to names.c, and adding the following code to arrays.c). It is not finished yet, but I would like to solicit some comments, as there are a few areas of R's internals that I am still feeling my way around. Firstly: 1) Would there be interest in adding a new operator %^% that performs

Greetings, Sorry, the last message was sent by mistake! Here it is again: I encounter a strange problem computing some numerical integrals on [0,oo). Define $$ M_j(x)=exp(-jax) $$ where $a=0.08$. We want to compute the $L^2([0,\infty))$-inner products $$ A_{ij}:=(M_i,M_j)=\int_0^\infty M_i(x)M_j(x)dx $$ Analytically we have $$ A_{ij}=1/(a(i+j)). $$ In the code below we compute the matrix

Dear All, Suppose I have a vector X = (x_1, x_2, ...., x_n), X_sort = sort(X) = (x_(1), x_(2), ... , x(n) ), and I would like to know the original position of these ordered x_(i) in X, how can I do it? case 1: all values are unique x <- c( 3, 5, 4, 6) x.sort <- sort(x) # # I would like to obtain a vector (1, 3, 2, 4) which indicates that 3 in x is still the 1st element in x.sort, 5 is at

Dear R users, I'd like to compute X like below. X_{i,t} = 0.1*t + 2*X_{i,t-1} + W_{i,t} where W_{i,t} are from Uniform(0,2) and X_{i,0} = 1+5*W_{i,0} Of course, I can do this with "for" statement, but I don't think it's good idea because "i" and "t" are too big. So, my question is that Is there any better idea to avoid "for" statement

I tried to manually assign each of 3 arrays a unique TBAA node. But it does not seem to help: alias analysis still considers arrays as may-alias, which most likely prevents the desired optimization. Below is the sample code with TBAA metadata inserted. Could you please suggest what might be wrong with it? Many thanks, - D. marcusmae at M17xR4:~/forge/llvm$ opt -time-passes -enable-tbaa -tbaa

Dear all, I know that my question is somewhat special but I tried several times to solve the problems on my own but I am unfortunately not able to compute the following test statistic using the quantreg package. Well, here we go, I appreciate every little comment or help as I really do not know how to tell R what I want it to do^^ My situation is as follows: I have a data set containing a

Hi, there. How do I calculate the cross-product in the form of \sum_{i=1}^{n}X_{i}^{t} \Sigma X_{i} using R code without using do loop? X_{i} is the covariate matrix for subject I, \Sigma is the covariance matrix. Thanks for your help. Yulei [[alternative HTML version deleted]]

Dear mailing list, I have found some strange behaviour which I think relates to parent frames and eval. Can anyone explain what's going on here? First example: > test.parent.funcs_ function() { outer.var_ 5 subfunc1_ function() substitute( outer.var, envir=parent.frame()) print( subfunc1()) subfunc2b_ function() eval( quote( outer.var), envir=parent.frame()) print(