similar to: "R" and "S-plus"

Dear all, S+Finmetrics has a number of very specilised functions. I am particularly interested in the estimation of cointegrated VARs (chapter 12 of Zivot and Wang). In this context the functions coint() and VECM() stand out. I looked at package "dse1", but found no comparable functionality. Are there any other packages you could point me to? In general, are there efforts for

Hello List, I've done some cursory searching but (so far) have struck out. Does anyone know if the R version of the S+ FinMetrics package is available? Best, Bill Vedder

On the cover of Zivot and Wang's Modeling Financial Time Series with S Plus, there is a correlation plot that seems to indicate the strength of correlation with color-coded squares, so that more highly correlated stocks appear darker red. If anybody out there is familiar with the book or understands what I am talking about, I am curious as to whether or not there is a similar function in R

Hi all, Does anybody have the source code of stochastic volatility models in R or Matlab, for example, the Bayesian based or the simulation based SV estimations as described by Prof Eric Zivot in the following discussion? https://stat.ethz.ch/pipermail/r-sig-finance/2005q4/000501.html -------------- I am wondering what is the current status of estimating stochastic vol models and what's

Hi, I did not find any web page about using R in economics and econometrics so far. However, this does not mean that there is none (searching with google for "R" and "economics" gives many pages about economics and a name like Firstname R. Lastname on it ;-)). Does anybody in the list does know such a web page? If not, I will be happy if you, Ajay, could build and

Is there a function in R that is equivalent to S-PLUS's seriesMerge(x1, x2, pos="union") where x1, and x2 are of class timeSeries seriesMerge is in S-PLUS's finmetrics. I looked into R's mergeSeries (in fSeries part of Rmetrics) but I could not make it behave quite the same. In R it expected a timeSeries object and a matrix of the same row count. In S-PLUS when using the

Finmetrics (in S-PLUS) has teh functions "positions" (return the positions of an ordered data object). Is there an equivalent to it in Remtrics? I am applying it to teh data of a time series.

please !, what is the R equivalents for the S-plus package : S+FinMetrics thanks hassan [[alternative HTML version deleted]]

Hi, Am I interpreting the results properly? Are my conclusions correct? > KPSS.test(df) ---- ---- KPSS test ---- ---- Null hypotheses: Level stationarity and stationarity around a linear trend. Alternative hypothesis: Unit root. ---- Statistic for the null hypothesis of level stationarity: 1.089 Critical values: 0.10 0.05 0.025 0.01 0.347 0.463

Greetings, Are there R packages that perform time-series analyses - particularly estimation of ARIMA models along with unit-root tests? I know that FinMetrics in the S-Plus program will do it, but I'm looking for R packages, as well any reference material for estimating time-series' models in R. Thanks in advance, David --

Hi, I am trying to figure how to use dlm with constant terms (possibly time-dependent) added to both equations y_t = c_t + F_t\theta_t + v_t \theta_t = d_t + G_t\theta_{t-1} + w_t, in the way that S-PLUS Finmetrics does? Is there any straightforward way to transform the above to the default setup? Thanks, Tsvetan -------------------------------------------------------- NOTICE: If received in

Hi, I am trying to fit a GARCH(1,1) model to a financial timeseries using the 'garch' function in the tseries package. However the parameter estimates obtained sometimes match with those obtained using SAS or S-Plus (Finmetrics) and sometimes show a completely different result. I understand that this could be due to the way optimization of MLEs are done, however, I would appreciate any

Dear r list, I posted this on the S list last week since i'm using some of the FinMetrics functions on copula. Knowing there is a copula package in R, I figure this would be an appropriate forum to ask this question. I want to model inverse relationship between two (non-normal, non-symmetric) marginals with the gumbel copula, or with any copula. Say, x is lognormal and y is norm. Since

Hi, I am trying to create a perspective plot with Time on the x-axis, Underlying Price on the y-axis, and Option Price on the z-axis. But I don't like the way my x-axis is setup. Right now, Time is this sequence. Time = seq(from = 1/52, to = 1, by=1/52) That results in the x-axis going from 0 at the back, to 1 near the foreground corner.(If that makes any sense) I want to do the

Hello, Does someone out there ever heard about PRAD or V5.2. Is there any link with Digium's TE110P? Thanks for any enlightments Lamine

I've looked around but I can't find the method in R for testing whether the resulting estimated coefficients of an AR model imply that the model is invertible. To quote from eric zivot's blue book : " the AR(p) is invertible provided the rots of the characteristic equation Phi(z) = 1 - phi_1*z - phi_2*z^2 = phi_3*z^3 - ..... Phi_p*z^p = 0 lie outside the complex circle".

Hi, (apologies for cross-posting) SolutionMetrics is presenting Introductory & Intermediate R and S+ courses in Brisbane, Melbourne & Sydney - March & April 2013. S+ FinMetrics course in Sydney - June 2013. More info below. Course Schedule - Click Here<http://bit.ly/13lJ4ag> To book, please email enquiries@solutionmetrics.com.au<mailto:enquiries@solutionmetrics.com.au>

I have a monthly price index series x, the related return series y = diff(log(x)) and a POSIXlt date-time variable dp. I would like to apply annual blocks to compute for example annual block maxima and mean of y. When studying the POSIX classes, in the first stage of the learning curve, I computed the maximum drawdown of x: > mdd <- maxdrawdown(x) > max.dd <- mdd$maxdrawdown > from

Dear list and Martin, I'm testing different approaches to fit an electricity demand time series and come upon the fracdiff package (v 1.3-1) for fitting fractional ARIMA models. The following questions are motivated by this package. 1. Despite having a help page, the residuals and fitted functions don't seem to have implementation, or did i miss something obvious? Alternatively, having a

I have been comparing the output of an R package to S+Finmetrics and I notice that the covariance matrix outputted by the two procedures is different. The R package computes the covariance matrix using Method 1 and I think ( but I'm not sure ) that S+Finmetrics computes it using Method 2. I put in a correctionfactor (see below ) in to Method 2 in order to deal with the fact that the var