similar to: R 'arima' discrepancies

Hello all, I have been using R's time series capabilities to perform analysis for quite some time now and I am having some questions regarding its reliability. In several cases I have had substantial disagreement between R and other packages (such as gretl and the commercial EViews package). I have just encountered another problem and thought I'd post it to the list. In this case,

On Mon, 24 May 2004 12:00:46 +0200 v.demartino2@virgilio.it wrote: > Working - among other things- in the field of (short & long term) electricity > forecast, * * * > we have to comply with the Tramo-seats closed-source procedure (http://www.bde.es/informes/be/docs/dt0014e.pdf) > to deal with seasonality of electricity monthly time-series, in line with > the methodology

Dear HelpeRs, I wonder if anyone knows of ways to read EViews file types. I did not find a function in the package 'foreign' and a search query submitted to http://search.r-project.org was not successful. Any hint is very much welcome. Dietrich Trenkler -- Dietrich Trenkler c/o Universitaet Osnabrueck Rolandstr. 8; D-49069 Osnabrueck, Germany email: Dietrich.Trenkler at

Working - among other things- in the field of (short & long term) electricity forecast, we are now using too many & too expensive pieces of licensed software: SAS, SPSS, EViews. This "sedimentation" is due to the fact that my predecessors in the past used different consultant companies to manage each procedure. Having attended the useR2004! Conference with the aim of assessing

Hi, I am doing PCA on several columns of data in a data.frame. I am interested in particular rows of data which may have a particular combination of 'types' of column values (without any pre-conception of what they may be). I do the following... # My data table. allDat <- read.table("big_select_thresh_5", header=1) # Where some rows look like this... # PDB SUNID1

Hi All, I am doing econometric modeling of panel data (fixed effects). We currently use Eviews to do this, but I have discovered a bug in Eviews 7 and am exploring the use of R to build panel data models / longitudinal data models. I looked at the plm package but do not see how I can incorporate AR terms in the model using the plm package. I have an Eviews model with two AR terms, AR(1) and

Hello!!, for linear models fit I use Gretl, but now I'm starting to use R, I would like to know if is there some function to obtain a extended summary like in Gretl. I will write a example in Gretl Modelo 1: MCO, usando las observaciones 1968-1982 (T = 15) Variable dependiente: Invest Coeficient St error t-ratio p-value const 377,631 35,0955 10,7601 <0,00001 *** GNP

hi all i have a question that about the eigen analysis found in R and in eviews. i used the same data set in the two packages and found different answers. which is incorrect? the data is: aa ( a correlation matrix) 1 0.9801 0.9801 0.9801 0.9801 0.9801 1 0.9801 0.9801 0.9801 0.9801 0.9801 1 0.9801 0.9801 0.9801 0.9801 0.9801 1 0.9801 0.9801 0.9801 0.9801 0.9801 1 now > svd(aa) $d [1] 4.9204

Dear all, I met with some problems when dealing with a time series with serial correlation. FIRST, I generate a series with correlated errors set.seed(1) x=1:50 y=x+arima.sim(n = 50, list(ar = c(0.47))) SECOND, I estimate three constants (a, b and rho) in the model Y=a+b*X+u, where u=rho*u(-1)+eps library(nlme) gls(y~x,correlation = corAR1(0.5)) # Is it the right procedure?

Hola!! A ver si alguien puede ayudarme!! Para ajuste de modelos lineales normalmente uso Gretl. Ahora estoy empezando a hacerlo en R. Me gustaría saber si existe alguna función que haga un summary extendido como el de Gretl. Os pongo un ejemplo del summary de Gretl. Modelo 1: MCO, usando las observaciones 1968-1982 (T = 15) Variable dependiente: Invest              Coeficiente   Desv. Típica

I am not an R-Head, hence I use nice utilities that integrate R into SPSS I have SPSS v24, R3.20 and R3.40 I have run IBM SPSS R Integration which requires linking to R3.20 I have installed R Factor v2.4.2 This package requires 'polycor' library Unfortunately, 'polycor' does not exist in R3.20 DATASET ACTIVATE DataSet1. *M?rio Basto, Jos? Manuel Pereira, IPCA *Required: SPSS 21

Hi all, This question is not really R related, rather on Statistics subject itself. Even I did not do those using R. however still I want to post it here, because my hope is I could get help from great statisticians who are the very active member of this group. My problem is to interpret Variance decomposition of VAR model in layman's language. Using EViews I got following : Variance

Dear all, I am trying to conduct an enhanced version of factor analysis with a SPSS interface that allows to use R. This approach has been suggested in the recent article: Basto, M. and J.M. Pereira An SPSS R-Menu for Ordinal Factor Analysis. Journal of Statistical Software 46, pp. 1-29. My variables are ordinal-type and the tool of Basto allows to run polychoric correlations in the SPSS

GDAL Package for R http://sourceforge.net/projects/rgdal The R GDAL package is an interface for accessing Frank Warmerdam's Geographic Data Abstraction Library from within R. GDAL is capable of reading and writing a wide range of geographic data formats including ESRI grid format and geotiff. On Wed, 2004-11-17 at 09:09, Witold Eryk Wolski wrote: > <SNIP> > SourceForge.net

Dear Sir, First of all Happy Holidays!,... I am writing to you because I am a bit confused about ARCH estimation. Is there a way to find what garch() exactly does, without the need of reading the source code (because I cannot understand it)? In Eviews (the results at the end) I am getting different results than in R (for those that have the program I do: Quick -> Estimage Equation ->

In the context of calling R from another program (namely gretl, http://gretl.sourceforge.net ) I'm trying to understand the interactions of the R init file (corresponding to the environment variable RPROFILE) and the source() function. I'll illustrate my problem with the following simplified contrast implemented in the bash shell (with R 2.7.1). 1. Works fine: allin at myrtle:~/Rfoo$

Hello, I have time series and need to draw simple and partial correlograms with associated Q-statistics (the same as in EViews). Can I do it in R? Thanks --------------------------------- [[alternate HTML version deleted]]

Dear Berger and Jim Can you see my eviews example in the annex? (scattersample.jpg) Sincerely Engin 2017-11-27 13:27 GMT+03:00 Eric Berger <ericjberger at gmail.com>: > LOL. Great reply Jim. > (N.B. Jim's conclusion is "debatable" by a judicious choice of seed. e.g. > set.seed(79) suggests that making the request more readable will actually > lower the number of

Hi, I have a problem with a regression I try to run. I did an estimation of the market model with daily data. You can see to output below: /> summary(regression_resn) Time series regression with "ts" data: Start = -150, End = -26 Call: dynlm(formula = ror_resn ~ ror_spi_resn) Residuals: Min 1Q Median 3Q Max -0.0255690 -0.0030378 0.0002787

Hi to all, In other statistical software, such as Eviews, it is possible to regress a model with the Least Squares method, assuming that the residuals follow an AR(q) process. For example the resulting regression is something like y = 1.2154 + 0.2215 x + 0.251 AR(1) How is it possible to do the same in R? Thank you very much in advance, Constantine Tsardounis http://www.costis.name