similar to: linear model with arma errors

hello, I created a package with my functions, and i wand to hide the code of some functions. Could you help me ? Gr?gory -------------------------------------------------------------- GAZ DE FRANCE Gr?gory Benmenzer DIRECTION DE LA RECHERCHE P?le Economie Statistiques et Sociologie 361 Avenue du pr?sident Wilson - BP 33 93211 La Plaine Saint Denis cedex tel : 01 49 22 55 07 fax : 01 49 22

hello, you can use the persp() function. The shade=0.7 option is very nice. With matlab, it is possible to change of colors automaticalli with the value to be plotted. Does someone know to do that ? Gr?gory f0z6305 at labs.tamu.edu@stat.math.ethz.ch on 06/02/2003 07:05:04 Envoy? par : r-help-admin at stat.math.ethz.ch Pour : r-help at stat.math.ethz.ch cc : Objet : [R] About

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

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

Hi, I'm trying to model an ARMA(1,[1,4]), i.e. I want only lags 1 and 4 of the Moving Average part. It's the '[1,4]' part that is giving me a problem. I've tried different arma's and arima's in different packages, namely: packages tseries, fArma, FinTS, timeSeries, TSA, Zelig, ds1, forecast For example, with package FinTS: > ( ARIMA(y, order=c(1,0,c(1,4))) )

When I do ARMA(2,2) using one lag of LCPIH data This is eview result > > *Dependent Variable: DLCPIH > **Method: Least Squares > **Date: 08/12/11 Time: 12:44 > **Sample (adjusted): 1970Q2 2010Q2 > **Included observations: 161 after adjustments > **Convergence achieved after 14 iterations > **MA Backcast: 1969Q4 1970Q1 > ** > **Variable Coefficient Std.

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;

Hi all, I want to fit the following model to my data: Y_t= a+bY_(t-1)+cY_(t-2) + Z_t +Z_(t-1) + Z_(t-2) + X_t + M_t i.e. it is an ARMA(2,2) with some additional regressors X and M. [Z_t's are the white noise variables] So, I run the following code: for (i in 1:rep) { index=sample(4,15,replace=T) final<-do.call(rbind,lapply(index,function(i)

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

Hello, The "arma" function in the "tseries" package allows estimation of models with specific "ar" and "ma" lags with its "lag" argument. For example: y[t] = a[0] + a[1]y[t-3] +b[1]e[t-2] + e[t] can be estimated with the following specification : arma(y, lag=list(ar=3,ma=2)). Is this possible with the "arima" function in the

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, 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

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

R-guRus , ARMA function in tseries, seems to be calculating the AR coeff 's as coef <- lm(xx[,1]~xx[,lag$ar+1])$coef [*snipped* from around line 77,] I'd like to modify this model with another term somewhat in these lines lm(xx[,1] ~xx[,lag$ar+1]+mvgsignal)$coef where mvgsignal is a moving average signal based on some indicators, the question is could i simply hack into

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

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:

Hello. I've got a problem with arma/xreg. I would like to get a better model-fit by implenting some external explanatory variable, so I thought I can implement it by expand the arima-function with an xreg-argument: I have two stationary data vectors y and x of length 201: y <-

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 R users, I have an unbalanced panel with an average of I=100 individuals and a total of T=1370 time intervals, i.e. T>>I. So far, I have been using the plm package. I wish to estimate a FE model like: res<-plm(x~c+v, data=pdata_frame, effect="twoways", model="within", na.action=na.omit) ?where c varies over i and t, and v represents an exogenous impact on x

When I run predict.Arima in my code, I get warnings like: Warning message: In cbind(intercept = rep(1, n), xreg) : number of rows of result is not a multiple of vector length (arg 1) I think this is because I'm not running predict.Arima in the same environment that I did the fit, so the data object used in the fit is no longer present. Looking at the predict.Arima source,