similar to: New forecasting bundle of packages

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]]

Hi R-users, I have a question relating to the HoltWinters() function. I am trying to forecast a series using the Holt Winters methodology but I am getting some unusual results. I had previously been using R for Windows version 2.7.2 and have just started using R 2.9.1. While using version 2.7.2 I was getting reasonable results however upon changing versions I found I started to see unusual

R gurus, I've exhausted my search of online help. This is my last resort. We're running R-2.1.1. I've been told by one of the R users here that we cannot upgrade to the lastest version because of some python rpy wrapper dependency that hasn't caught up to the latest version of R. The software is running on Solaris 10 x86. Gcc version is 3.4.1. R is installed in

Dear All, I was wondering why the forecast for an additive HoltWinters model is given by Yhat[t+h] = a[t] + h * b[t] + s[t + 1 + (h - 1) mod p]. I am a student and new to time series analysis and forecasting. That said, I considered t = 13 and h = 1: Yhat[13+1] = a[13] + b[13] + s[13 + 1] It seems odd that to predict Yhat[14], you would need a s[14] which in turn depends on Y[14], given that

I want to forecaste the call number everyday for a call-center. Now I have removed the influence of the fluctuation with some method, so only thing left is to analyze the trend of the call number every day. I have thought of two ways: regression and HoltWinters smooth. But when I use regression, I find some day's call number will bcome negative, which is obviously unreasonabe. If I use

CRAN (and crantastic) updates this week New packages ------------ Updated packages ---------------- New reviews ----------- This email provided as a service for the R community by http://crantastic.org. Like it? Hate it? Please let us know: cranatic at gmail.com.

Hi all, I have some residuals from regression, and i suspect they have correlations in them... I am willing to cast the correlation into a ARMA(p, q) framework, what's the best way to identify the most suitable p, and q, and fit ARMA(p, q) model and then correct for the correlations in regression? I know there are functions in R, I have used them before, but I just want to see if I can do

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

1. This is an imaginary data on monthly outcomes of 2 years and I want to forecast the outcome for next 12 months of next year. data Data1; input Yr Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec; datalines; 2008 12 13 12 14 13 12 11 15 10 12 12 12 2009 12 13 12 14 13 12 11 15 10 12 12 12 ; run; I converted the above data into the below format to use it in R as it was giving error: asking

I suggest, you read: Forecasting: principles and practice from Hyndman-Athana?sopou?los https://www.otexts.org/fpp

Hi. I have to forecast a time series of a Internet network traffic bitrate. The data are in file http://www.forumaltavilla.it/joomla/datitesi/dati.datand the sampling time is every 0.05 seconds. Now, i want to use HoltWinters forecasting. This is my script. dt=1.58443823e-9 #0.05 seconds in years dati.ts=ts(scan("dati.dat"),start=0,deltat=dt) model=HoltWinters(dati.ts)

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>

Hi, I tried to use the Croston function from the forecasting package 1.24<http://robjhyndman.com/software/forecasting> with the code below, but I get in return this message "*Error in decompose(ts(x[1L:wind], start = start(x), frequency = f), seasonal) : time series has no or less than 2 periods*". histValues

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

I'm trying to fit a mixed-effects model of the form Y = a + bX + cZ + e where X are fixed effects and Z are random. i.e., c is a vector of random coefficients with mean 0. There is no "grouping" variable such as would be used with longitudinal data. Can the nlme package handle this sort of thing? Although it is a simpler model than would be used with grouped data, I can't seem

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

Dear R-helpers, I would appreicate if someone can help me on the transfer parameter in ARIMAX and also see what I am doing is correct. I am using ARIMAX with 2 Exogeneous Variables and 10 years data are as follows: DepVar Period, depVar, IndepVar1 Period, indepVar1, IndepVar2 Period, indepVar2 Jan 1998,708,Jan 1998,495,Jan 1998,245.490 Feb 1998,670,Feb 1998,421.25,Feb 1998,288.170 Mar

Dear all: I'm a newbie and an amateur seeking help with forecasting the next in a non-stationary time series, with constraints of 1 (low) and 27 (high) applicable to all. What I need help with is the solution concept. The series has 439 observations as of last week. I'd like to analyze obs 1 - 30 (which are historical and therefore invariate), to solve for 31. The history: Obs 1

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