similar to: FinTS_0.3-1

Hi, All: FinTS version 0.2-7 is now available on CRAN. This version adds two new functions: * ArchTest to compute the Engle (1982) Lagrange multiplier test for conditional heteroscedasticity, discussed on pp. 101-102 of Tsay, with examples on those pages worked in the R script in "~R\library\FinTS\scripts\ch03.R", where "~R" is your local R installation directory.

Hi, All: FinTS version 0.2-7 is now available on CRAN. This version adds two new functions: * ArchTest to compute the Engle (1982) Lagrange multiplier test for conditional heteroscedasticity, discussed on pp. 101-102 of Tsay, with examples on those pages worked in the R script in "~R\library\FinTS\scripts\ch03.R", where "~R" is your local R installation directory.

Hi, I'm slowly working through Tsay's "Analysis of Financial Time Series" 3rd ed. ?I'm trying to replicate Table 2.1 on p.47, which gives PACF, AIC, and BIC for the monthly simple returns of the CRSP value-weighted index. The data: http://faculty.chicagobooth.edu/ruey.tsay/teaching/fts3/m-ibm3dx2608.txt > da <-

I have friendship data which is strong skewed. So it doesn't make sense to use maximum likelihood methods for fa and cfa. But I couldn't find any function for asymptotically distributed data for doing a factor analysis. Only: apca() but there is no possibility to allow for factor correlations. The same problem is with sem() I couldn't get any solutions for my model because of the

I am new to using R and would appreciate some advice on which books to start with to get up to speed on using R. My Background: 1-C# programmer. 2-Programmed directly using IMSL (Now Visual Numerics). 3- Used in past SPSS and Statistica. I put together a list but would like to pick the "best of" and avoid redundancy. Any suggestions on these books would be helpful (i.e. too much

Hi, I was trying to repeat the estimation of threshold GARCH models from the book "Analysis of Financial Time Series" by Ruey S. Tsay, and I was succesfull, but I had to use "for" loop, which is quite slow. The loop is necessary, since you need to calculate recursive sequence. Is there a faster way to do this in R, without using loops? The model is such: r_t = \mu + \alpha_2

Hi all, I am looking for study resources for (financial) time series? Hopefully I could find video lectures then it will reduce the learning curve. Thanks a lot! [[alternative HTML version deleted]]

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))) )

> > Hi there fellow R-Users, > > > > Can anyone recommend a good book on the theory and practice > > of applying > > GARCH models. > Hello Wayne, * Campbell, John, Lo, Andrew W., MacKinlay, A. Craig, The Econometrics of Financial Markets, 1996, Princeton, NJ: Princeton University Press. http://pup.princeton.edu/titles/5904.html * Enders, Walter,

Hi all, Please recommend good books for the following three categories. (I am aim at finance, macroeconomics, trading and business applications). (1) statistical (financial) data analysis; (2) time series; (3) econometrics. More specifically, I am looking for the following two types of books: (1) Books that provide big pictures and intuitions and books that connect dots... For example, there

----------------------------------------------------------------------------------------- Packages for the computation of optimally robust estimators ----------------------------------------------------------------------------------------- We would like to announce the availability on CRAN (with possibly a minor delay until on every mirror) of new versions of our packages for the computation of

anacor-0.9.0 is on CRAN (by De Leeuw and Mair) anacor does correspondence analysis and canonical correspondence analysis. It can make row plots, column plots, joint plots, Benz?cri plots, regression plots, and transformation plots. Where appropriate, plots can be in 3d using either rgl or scatterplot3d. Row and column points can be in standard scaling, Benz?cri scaling, Goodman scaling,

On Tue, Oct 13, 2009 at 5:06 PM, Rolf Turner <r.turner@auckland.ac.nz>wrote: > > Not clear to me what the OP really wants. Perhaps the seasonal > model is what's required; perhaps an arima(1,0,4) model with > theta_2 and theta_3 constrained to be 0. The latter can be > achieved with > > arima(x,order=c(1,0,4),fixed=c(NA,NA,0,0,NA,NA)) > > Or perhaps

Hello all, This is a request for help from somebody who has the Ox interfaces working in R. I am trying to get the Ox interfaces working for Arfima and Garch modelling. However, I am having several problems: 1. The link to download G at rch_v40 does not work. Does anybody have a copy to email to me please? 2. Various guides offer different instructions for installing Ox in the correct place

Dear R Helpers, I try to write a small package that based on nlme however my code does not work. R always appears this message: Error in eval(expr, envir, enclos) : object "y" not found where y is the response variable. Please help me out! This is my code: require(nlme) AMPmixed<-function(y, x, S1=c("asymptotic","logistic"), random,data,

Dear all, I'm using R 2.8.1 under Windows Vista on a dual core 2,4 GhZ with 4 GB of RAM. I'm trying to reproduce a result out of "Analysis of Financial Time Series" by Ruey Tsay. In R I'm using the fGarch library. After fitting a ar(3)-garch(1,1)-model > model<-garchFit(~arma(3,0)+garch(1,1), analyse) I'm saving the results via > result<-model

I'm trying to use a paper by Hardin & Rocke: http://handel.cipic.ucdavis.edu/~dmrocke/Robdist5.pdf as a guide for a function to identify outliers in multivariate data. Attached below is a function that is my attempt to reproduce their method and also a test to see what fraction of the data are identified as outliers. Using this function I am able to reproduce their results regarding the

I made one typo in my previous mail.   May I ask one statistics related question please? I have one query on MLE itself. It's property says that, for large sample size it is normally distributed [i.e. asymptotically normal]. On the other hand it is "Consistent" as well. My doubt is, how this two asymptotic properties exist simultaneously? If it is consistent then asymptotically it

Hi, Does anyone know if R has a Lagrange multiplier (LM) test for ARCH effects for univariant time series? Thanks! -- Tom [[alternative HTML version deleted]]

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