similar to: Loading C++ libraries

Is there a function ".C++(...)" for R, or does anybody know how to dynamically load C++ functions into R? lg at -- Adrian Trapletti, Vienna University of Economics and Business Administration, Augasse 2-6, A-1090 Vienna, Austria Phone: ++43 1 31336 4561, Fax: ++43 1 31336 708, Email: adrian.trapletti at wu-wien.ac.at

tseries_0.3-0 at CRAN now contains the following new features: NelPlo Nelson-Plosser Macroeconomic Time Series garch Fit GARCH Models to Time Series get.hist.quote Download Historical Finance Data jarque.bera.test Jarque-Bera Test na.remove NA Handling Routines for Time Series garch contains a GARCH estimation routine together

tseries_0.3-0 at CRAN now contains the following new features: NelPlo Nelson-Plosser Macroeconomic Time Series garch Fit GARCH Models to Time Series get.hist.quote Download Historical Finance Data jarque.bera.test Jarque-Bera Test na.remove NA Handling Routines for Time Series garch contains a GARCH estimation routine together

There seems to be a problem with plot.ts (R Version 0.64.2) >x<-cbind(1:10,2:11) >x<-as.ts(x) >plot(x) Error: subscript (20) out of bounds, should be at most 10 > The problem is located in "[.ts": > x<-cbind(1:10,2:11) > x[is.finite(x)] [1] 1 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 11 > x<-as.ts(x) > x[is.finite(x)] Error: subscript

Fritz, I have slightly adapted (didn't work before) "tsboot" from the "boot" library to the current time series conventions of R. The following patch will do that. I suggest to apply this patch to the file "boot/R/bootfuns.q" of the "boot" library at CRAN. best Adrian --- bootfuns.orig.q Thu Dec 9 10:07:23 1999 +++ bootfuns.q Thu Dec 9 10:06:51 1999

Fritz, I have slightly adapted (didn't work before) "tsboot" from the "boot" library to the current time series conventions of R. The following patch will do that. I suggest to apply this patch to the file "boot/R/bootfuns.q" of the "boot" library at CRAN. best Adrian --- bootfuns.orig.q Thu Dec 9 10:07:23 1999 +++ bootfuns.q Thu Dec 9 10:06:51 1999

Fritz just put tseries_0.3-1 on CRAN. It should now be more compatible across different platforms than 0.3-0. Thanks to Brian Ripley, Karl Syring, and Dirk Eddelbuettel. Adrian -- Adrian Trapletti, Vienna University of Economics and Business Administration, Augasse 2-6, A-1090 Vienna, Austria Phone: ++43 1 31336 4561, Fax: ++43 1 31336 708, Email: adrian.trapletti at wu-wien.ac.at

Is there a way to efficiently read large datasets directly into a matrix byrow? I know data.frame, but for large datasets it doesn't efficiently work, also if I increase the cons memory. R --nsize 1000k --vsize 90M ... > x<-read.table("pendler.luft.txt") Error: cons memory (1000000 cells) exhausted See "help(Memory)" on how to increase the number of cons

I would like to use the call_R mechanism. Unfortunately I don't fully understand what the arguments are from the example in "R-0.64.2/demos/dynload". Could anybody explain me how I have to define the arguments, e.g., I want to call R with 5 doubles (or double[5]) and func does not return a value (is that possible or is it necessary to return at least a dummy?). This is from the

Fritz just put the updated tseries package to CRAN. I mainly removed (and corrected) code such that tseries fits together with package ts. New code is White's and Teraesvirta's tests for neglected non-linearity (also for the regression case). From the INDEX file: NelPlo Nelson-Plosser Macroeconomic Time Series adf.test Augmented Dickey-Fuller Test amif

Fritz just put the updated tseries package to CRAN. I mainly removed (and corrected) code such that tseries fits together with package ts. New code is White's and Teraesvirta's tests for neglected non-linearity (also for the regression case). From the INDEX file: NelPlo Nelson-Plosser Macroeconomic Time Series adf.test Augmented Dickey-Fuller Test amif

Fritz just put the first version of a new time series package to the contrib section at CRAN. The package is called "tseries.tgz" and provides a library for time series analysis. It contains acf Autocorrelation Function adf.test Augmented Dickey-Fuller Test amif Auto Mutual Information Function bds.test BDS Test

Fritz just put the first version of a new time series package to the contrib section at CRAN. The package is called "tseries.tgz" and provides a library for time series analysis. It contains acf Autocorrelation Function adf.test Augmented Dickey-Fuller Test amif Auto Mutual Information Function bds.test BDS Test

Does anybody understand what's going on here: I have the following ascii file called "y.txt" "USD-DEM" "USD-JPY" "DEM-JPY" 0.344901 4.78712 4.442 0.345715 4.7882 4.44189 0.350657 4.79065 4.44177 0.35347 4.79065 4.43616 0.35368 4.78957 4.43622 0.35361 4.78982 4.43669 0.353821 4.79036 4.43622 0.352767 4.78899 4.43634 0.353119 4.78916 4.43545

In the "Writing R Extensions" manual appears this example, to get access to C++ function using the R commands: R> dyn.load(paste("X", .Platform$dynlib.ext, sep = "")) constructor Y R> .C("X_main") constructor X destructor X list() That gives me access to the function "X_main", but how to get access to methods and properties

Hi folks, My system is Windows98 + R1.9.0. The path for my system is c:\perl\bin; c:\mingw\bin; c:\rtools; c:\windows; c:\windows\command; c:\rw1090\bin. I created three files followed the examples in “Writing R extensions” in the directory c:\temp: // X.hh class X { public: X (); ~X (); }; class Y { public: Y (); ~Y (); }; // X.cc #include <iostream> #include "X.hh" static

Martyn Plummer wrote: > Dear Adrian, Hi Martin > > > Thank you for providing your time series library for R. I have been > working on a time series package myself, with help from Paul Gilbert. It > is called "bats" (doesn't stand for anything except possibly "basic time > series") and can be found in the devel directory on CRAN. > > The

Hi, I am trying to set up a C++ library for my R code. I followed the R-extension manual but found out that the example of "X.cpp, X_main.cpp" is somewhat too simple. Here is my code: //lib4R.h testing for interfacing C++ with R -- using C++ library in R #include <iostream> using namespace std; class lib4R { public: lib4R(); ~lib4R(); int

Folks, I'm fairly sure that I'm doing something stupid, but I'm getting a few really strange results from *some* of the distributions, but by no means all, when I link directly to the R shared library. I've tried this on both Windows with the precompiled Mingw binary of R-2.5.0 (compiling my code with MinGW-3.4.2), and by building R-2.5.0 on Mandriva Linux with gcc-3.4.4 and

We are using the --enable-maintainer-mode and will move to git soon. The diff file is attached. *Siddhant Mutha* Undergraduate Student Department of Computer Science and Engineering IIT Madras Chennai http://www.siddhantmutha.com/ <http:/www.siddhantmutha.com/> On Sun, Apr 13, 2014 at 8:26 PM, James Aylett <james-xapian at tartarus.org>wrote: > On 13 Apr 2014, at 15:48, Pallavi