similar to: stats::kernel

I have a suggestion for kernapply for ts objects. When we choose the option circular=F, the returned series don't have the correct dates. The removed dates are all at the beginning instead of half at the beginning and half at the end. It is particularly useful when we need to smooth the series (or remove a trend using a filter) before estimating a model (like in macroeconomics) or simply

Hi all, I found a discrepancy between the sum() in R and either a sum done in C or Fortran for vector of just 5 elements. The difference is very small, but this is a very small part of a much larger numerical problem in which first and second derivatives are computed numerically. This is part of a numerical method course I am teaching in which I want to compare speeds of R versus Fortran (We

Hi all, I am looking for a function similar to mclapply() that would work with GPU cores. I have looked at all possible packages related to GPU computing but they are mainly providing functionality for big dataset or big matrices. I use mainly mclapply to speed up simulations by running several simulations in parallel, which works nicely. Is it possible to do the same with a multicore GPU? I

My simple functions were to compare the result with the gfortran compiler sum() function. I thought that the Fortran sum could not be less precise than R. I was wrong. I am impressed. The R sum does in fact match the result if we use the Kahan algorithm. P. I am glad to see that R sum() is more accurate than the gfortran compiler sum. On 16/03/18 11:37 AM, luke-tierney at uiowa.edu wrote:

This question concerns rpart's facility for user-defined functions that accomplish splitting. I was interested in modifying the code so that in each terminal node, a linear regression is fit to the data. It seems that from the allowable inputs in the user-defined functions, that this may not be possible, since they have the form: function(y, wt, parms) (in the case of the

Hi, I have a suggestion for the fonction arima and arima0. I think you should not call the constant an intercept because it creates confusion. It is not really an intercept but a mean. For an AR(1) the intercept mu should be defined as: X(t)=mu + phi X(t-1) + e(t) What you call intercept mu is rather defined as (X(t)-mu) = phi (X(t-1)-mu)) + e(t) which is not a common way to define an

We're having the first LLVM Social for those in or nearby the Kitchener/Waterloo/Cambridge area of Ontario! WHERE: Huether Hotel Barley Works in Uptown Waterloo [1] WHEN: Thursday, August 27, 7:00 PM I've reserved an area of the bar for the event under "LLVM Social". If you need any help, call me at 519-496-4224. Thanks to everyone who participated in the Doodle poll. We

Hello, I want to install hdf5 libraries for R and I get the same error as posted below whether I try install.packages("hdf5") from R command prompt or the command line installation below. I would appreciate if any one could help me on this. [alamj@thor hdf5]$ ./configure --with-hdf5=/bluejay/apps/HDF5-1.6.6/x86_64 checking for gcc... gcc checking for C compiler default output... a.out

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

Hello all, I use the arima to get a model, i.e. fit = arima(x,order=c(1,0,0)) and I know I can get the following from fit via est.coef = coef(fig) est.aic = fit$aic std.err = sqrt(diag(vcov(fit))) t.stat = est.coef/std.err How can I get the following stat from arima? Pr(>|t|) r2 adjust_r2 rmse Thanks, Rebecca

Hello, I am Mohammed Nafees, a Computer Science student at the University of Waterloo, Canada and I am going to apply for Google Summer of Code 2018. I am interested in working on the project "Reimplement LLDB's command-line commands using the public SB API. ". How can I start, and how can I contact the mentors? I have completed Google Summer of Code 2017 with KDE (project

I'm proposing to add something like this to the stats package : ---------------------------------------------------------- ### "The" sigma in lm/nls - "like" models: sigma <- function(object, ...) UseMethod("sigma") ## works whenever deviance(), nobs() and coef() do fine: sigma.default <- function (object, use.fallback=TRUE, ...)

On 2025-01-02 9:04 a.m., Norbert Kuder wrote: > Hello all, > > I am running R version 4.4.2 (2024-10-31 ucrt) on Windows 10 x64, and > noticed something that might be a minor bug (or at least inconsistent code) > in the stats/arima.R package. > I have found: > 1. A missing stop() call at line 69: > if (length(order) == 3) seasonal <- list(order = seasonal) else

Sorry for starting another topic, this is actually a reply to Segher's post on Sun Oct 22 on the 'mdct question' topic. I wasn't subscribed properly and so I didn't get email confirmation and thus can't add to that thread. So Segher, if the equation is indeed what you say it is, then replacing mdct_backward with this version should work, but it doesn't. Am I applying

On 2025-01-02 11:20 a.m., Duncan Murdoch wrote: > On 2025-01-02 9:04 a.m., Norbert Kuder wrote: >> Hello all, >> >> I am running R version 4.4.2 (2024-10-31 ucrt) on Windows 10 x64, and >> noticed something that might be a minor bug (or at least inconsistent code) >> in the stats/arima.R package. >> I have found: >> 1. A missing stop() call at line 69:

Dear R developers: I am trying to fit a PPO model using vglm from the library VGAM, and get an error while executing the code. Here is the data, code, and error: Data: first row is the column names. a = age, and 1,2,3, 4 and 5 are condition grades. a 1 2 3 4 5 1 1 0 0 0 0 2 84 2 7 10 2 3 16 0 6 6 2 4 13 0 3 4 0 5 0 0 0 1 0 Library(VGAM)

Hi there: i got a problem to get the prediction from a model recently. for example if i use a survival analysis to predict the risk. i use the code like below: i found the the prediction is not equal to (coef * x + coef * sex) , could someone help me with why this happened? and can someone explain to me how this command "predict(f, type="terms")" works? is every partial

I have a frequency table that I am trying to plot on a rose diagram using rosavent. I've set the table up by using this line: Wind_freq_speed <- t(table(cut(Wind_Dir_vec, 0:36), cut(Wind_Speed_vec, seq(0, to=60, by=10)))) It produces the following table layout, which is consistent with the rosavent example (windfreq.dat). 10 20 30 40 50 60 70... 360 0-10 10-20

Dear List, A posting to R-Help exposed this problem with the print method for objects of class Arima: > set.seed(1) > x <- arima.sim(n = 100, list(ar = 0.8897, ma = -0.2279)) > mod <- arima(x, order = c(1,0,1)) > coefs <- coef(mod) > mod2 <- arima(x, order = c(1,0,1), fixed = coefs) > mod2 Call: arima(x = x, order = c(1, 0, 1), fixed = coefs) Coefficients: Error

Hi, I have a question about the usage of eval(). Wonder if any experienced user can help me out of it. I use eval() in the following function: semireg.pwl <- function(coef.s=rnorm(1),coef.a=rnorm(1),knots.pos=knots.x,knots.ini.val=knots.val){ knotn <- length(knots.pos) def.par.env <- sys.frame(1) print(def.par.env) print(environment(coef.s)) tg <- eval( (parse(text=