similar to: Mixed-effects model problem.

I am trying to get a dll compiled for use with dyn.load. I use R.1.7.1 under Windows. I have tried the following trivial example based on the "Writing R extensions" manual. rtest.h -------- class X { public: X (); ~X (); void Give7(double*); }; class Y { public: Y (); ~Y (); }; rtest.cpp --------- #include <iostream.h> #include "rtest.h" static Y y;

I've been successfully using a dll via dyn.load() with R1.6.0 for Windows, but when I try it under R1.6.1 it manages to crash the program completely. Has there been a change in how R1.6.1 handles dynamic loading? I couldn't spot any such changes in the documentation. This problem occurred on two different machines, and both run the code under R1.6.0 without a problem. Rob Hyndman

Hi, can you advise me is there any ROC(Receiver Operating Characteristic)analysis program in R? Thanks, Dechao ===== Dechao Wang Tel: (44) 01223 719718 Mob: (44) 07729 411134 __________________________________________________ Everything you'll ever need on one web page from News and Sport to Email and Music Charts

Dear R-Users, How can I compute simple moving averages from a time series in R? Note that I do not want to estimate a MA model, just compute the MA's given a lenght (as excel does). Thanks ________________________________________ Ricardo Gonçalves Silva, M. Sc. Apoio aos Processos de Modelagem Matemática Econometria & Inadimplência Serasa S.A. (11) - 6847-8889 ricardosilva@serasa.com.br

Dear all, I'm looking for how can I estimate a linear model with ar(ma) errors : y(t)=a*X(t)+e(t) with P(B)e(t)=Q(B)u(t) where u is a white noise and P, Q are some polynomes. Could you help me ? Gr?gory Benmenzer

Has anyone got a function for smooth monotonic interpolation of a univariate function? I'm after something like the NAG function PCHIM which does monotonic Hermite interpolation. Alternatively, montononic cubic spline interpolation. Please reply directly. Rob Hyndman ___________________________________________________ Rob J Hyndman Associate Professor & Director of Consulting

I'm not sure who is responsible for quantile(), but I assume they read this list. Ivan Frohne and I have produced a revision of the quantile.default() function which enables the computation of alternative sample quantile definitions. The code and .Rd file are attached. This enables the user to produce quantiles that are equivalent to those in various statistics package. There is a type

The generic stats::median method is defined as median <- function (x, na.rm = FALSE) {UseMethod("median")} I suggest that this should become median <- function (x, na.rm = FALSE, ...) {UseMethod("median")} This would allow additional S3 methods to be developed with additional arguments. Currently I have to over-ride this generic definition in the demography

>>>>> Martin Maechler <maechler at stat.math.ethz.ch> >>>>> on Mon, 27 Feb 2017 10:42:19 +0100 writes: >>>>> Rob J Hyndman <Rob.Hyndman at monash.edu> >>>>> on Wed, 15 Feb 2017 21:48:56 +1100 writes: >> The generic stats::median method is defined as median <- >> function (x, na.rm = FALSE)

Hello, I have a several time series, which I would like to check for their best fitted Arima model (I am checking for the lowest aic value). Which lets me raise two questions: 1) is there are more efficient way, than using 6 for-loops? 2) sometimes the system cannot calculate with given parameters - is there a more efficient solution than I found? I hope, you can help me to make this

Can we please have a ... argument in median() to make it possible to pass arguments to specific methods. _____________________________ Rob J Hyndman Professor of Statistics, Monash University Editor-in-Chief, International Journal of Forecasting http://www.robhyndman.info/ [[alternative HTML version deleted]]

Dear R Users, I am working for the United Nations to construct a complete life table from an abridged table. I want to use the code of Hydman Filter by Rob J Hydman but an error sentence always appears and it simply doesn't run-- source("C:/R/Jamie/HymanFilter.R") Error in .C("spline_coef", method = as.integer(method), n = nx, x = x, : C symbol

Can anyone please recommend a good site for crime related time series? Thanks! Erin mailto: hodgess at uhddx01.dt.uh.edu -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To:

Using forecast package. http://www-personal.buseco.monash.edu.au/~hyndman/Rlibrary/forecast/ Best Regards. Message: 50 Date: Thu, 18 May 2006 18:50:15 -0400 From: "Wensui Liu" <liuwensui en gmail.com> Subject: To: Michael <comtech.usa en gmail.com> Cc: R-help en stat.math.ethz.ch Message-ID: <1115a2b00605181550i1e718124p3ec01f4f70ed9f02 en mail.gmail.com>

Hello R help I have been trying to use Rob Hyndman's monotonically increasing spline function. But like another user or two seem have a problem with a missing DLL (namely "spline_coef"). None of the previous help postings seemed to have any solutions to this problem. As per a Ripley suggestion I have deleted all previous versions of R and reinstalled R 2.7.0 and the problem

For some reason, the help file on quantile() says "Missing values are ignored" in the description of the x argument. Yet this is only true if na.rm=TRUE. I suggest the help file is amended to remove the words "Missing values are ignored". Rob _____________________________ Rob J Hyndman Professor of Statistics, Monash University Editor-in-Chief, International Journal of

v1.0 of the forecasting bundle of packages is now on CRAN and will propagate to mirrors shortly. The forecasting bundle of R packages provides new forecasting methods, and graphical tools for displaying and analysing forecasts. It comprises the following packages: * forecast: Functions and methods for forecasting. * fma: All data sets from Makridakis, Wheelwright and Hyndman

v1.0 of the forecasting bundle of packages is now on CRAN and will propagate to mirrors shortly. The forecasting bundle of R packages provides new forecasting methods, and graphical tools for displaying and analysing forecasts. It comprises the following packages: * forecast: Functions and methods for forecasting. * fma: All data sets from Makridakis, Wheelwright and Hyndman

>>>>> Rob J Hyndman <Rob.Hyndman at monash.edu> >>>>> on Wed, 15 Feb 2017 21:48:56 +1100 writes: > The generic stats::median method is defined as median <- > function (x, na.rm = FALSE) {UseMethod("median")} > I suggest that this should become median <- function (x, > na.rm = FALSE, ...)

Hi I have a 3 x 2 contingency table: 10 20 30 40 50 60 I want to update the frequencies to new marginal totals: 100 130 40 80 110 I want to use the ipf (iterative proportional fitting) function which is apparently in the cat package. Can somebody please advice me how to input this data and invoke ipf in R to obtain an updated contingency table? Thanks. By the way I am quite new to R. -- Dr