similar to: regarding chaos

Dear All; I have used fbmSim to simulate a fbm sequence, however, when I tried to estimate the Hurst effect, none of the nine procedures gave me an answer close enough to the real value, which is 0.5 (n=1000). So, would you please advice, 1. which is the best method to estimate the H among the 9 mehods, R/S, higuchi or Whittle? 2. how to choose the levels (default=50), minnpts, cutoff values or

What Dave said, plus here's a hint. Try this example (which uses base graphics): plot(1:5) plot(1:5, cex.lab=2) Then look at the help page for par help('par') or ?par to search for other graphics parameters (base graphics) you can use to change various things. Success will depend, as Dave indicated, on how the package author handled the plotting options in rsFit(). -Don --

> On Jan 26, 2018, at 9:51 AM, MacQueen, Don <macqueen1 at llnl.gov> wrote: > > What Dave said, plus here's a hint. Try this example (which uses base graphics): > > plot(1:5) > plot(1:5, cex.lab=2) > > Then look at the help page for par > help('par') > or > ?par > to search for other graphics parameters (base graphics) you can use to

Has anyone writen R code for estimating Hurst exponent with R/S method or other methods? or any other source of R code available? Many thanks Catherine Wang

Dear R Users, Can anyone point me to a package for R vrsion 2.7.1 which implements some Hurst exponent estimation methods ? Thanks in advance, Tolga Generally, this communication is for informational purposes only and it is not intended as an offer or solicitation for the purchase or sale of any financial instrument or as an official confirmation of any transaction. In the event you are

Hello, I'm using fArma package to estimate the value of Hurst exponent using R/S method. However, for a certain set of data I get H ~ 1.8. How do I interpret this? Following are the output that I get for this set: > mean(data[,2]) [1] 400.5433 > sd(data[,2]) [1] 1139.786 > > rsFit(data[,2], levels = 64) Title: Hurst Exponent from R/S Method Call: rsFit(x = data[, 2], levels

Hello, Has anybody transferred Bearn's S+ code to R ? Best, Costas -- ------------------------------------------------------------------------- Konstantinos E. Vorloou | Tel: +44 (0)191 374 1821 Department of Economics & Finance | Fax: +44 (0)191 374 7289 University of Durham, | email: K.E.Vorloou at durham.ac.uk 23/26 Old Elvet, | or : vorlow at

Hello, I am trying to calculate the autocovariance matrix for any general farima(p,d,q) with p,q > 1. Could anyone give an idea how to implement in R or if there is any package for this? thank you beforehand. Jose.

Dear All, I am a novice when it comes to time-series analysis and at the moment I am actually interested in calculating the Hurst exponent of a time series. This question has already been asked quite some time ago http://bit.ly/98dZsi and I trust some progress has been made ever since. I was able to find some functions in the packages http://cran.r-project.org/web/packages/Rwave/index.html

Hi, Can u please tell me which all packages do i need to install to estimate the hurst parameter in R. I have tried installing all the possible options but still it doesnt work. basically i want to use 9 functions to estimate hurst parameter like aggvarfit, rsfit, etc. i will be very thankful if u could be of some help. -- Regards, Deepak Jadhav. [[alternative HTML version

This small patch extends configure_socket_options to support FreeBSD''s accf_http(9), which defers accept() until there''s a full HTTP request to read. Seems to work fine on 6.1-STABLE. DragonflyBSD should work too provided the /freebsd/ line is modified to match it. accf_http(9): http://www.freebsd.org/cgi/man.cgi?query=accf_http&sektion=9 -- Thomas

Hello! I installed the fSeries package to get some farima time-series which i tried with farimaSim, but unfortunately i got always an error. I tried it this way: > farimaSim(n = 1000, model = list(ar = 0.5, d = 0.3, ma = 0.1), method="freq") Error in farimaSim(n = 1000, model = list(ar = 0.5, d = 0.3, ma = 0.1), : ... used in an incorrect context Some ideas? Regards, ___

Dear R Helpers, I have searched for any R package or code for simulating multivariate fractional Brownian motion (mFBM) or multivariate fractional Gaussian noise (mFGN) when a covariance matrix are given. Unfortunately, I could not find such a package or code. Can you suggest any solution for multivariate FBM and FGN simulation? Thank you for your help. Best Regards, Ryan ----- Wonsang You

Are there any packages that help with statistical analysis in situations where fractal geometry is relevant? Perhaps something that supports computation of fractal related statistics, such as the Hurst exponent or fractal dimension? Or perhaps which support obvious tasks such as taking samples from a dataset at different levels of granularity (such as sampling spatial data at cm, m, km

I tried updating the BIOS on my K8WE (S2895) yesterday to 1.03, but after the update, FreeBSD (RELENG_6 dated March 26) would randomly freeze after booting. As I was updating from v1.01, I suspect it may be the updates to the nVidia SATA firmware that caused the issue, as things generally froze shortly after the background fsck processed kicked in (with, obviously, the exception of the first

Hello, I am trying to collect several global measures or statistics for time-series as well as packages of R that can compute them. I have found several of them in papers and books, but the literature is so big i am sure i am missing several of them. skewness kurtosis min max mean SD trend seasonality periodicity chaos (Lyapunov Exponent) / Largest Lyapunov Exponent (i think is the same

Dear all, In many papers regarding time series analysis of acquired data, the authors analyze 'marginal distribution' (i.e. marginal with respect to time) of their data by for example checking 'cdf heavy tail' hypothesis. For i.i.d data this is ok, but what if samples are correlated, nonstationary etc.? Are there limit theorems which for example allow us to claim that

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

I''m running FreeBSD 6.1 and installed the 1.0.1.1 mongrel_cluster prerelease. I had a problem with the mongrels not stopping, and it turns out it''s because ps is reporting my processes as just [ruby18] instead of someting more like "mongrel_rails start -d ......." Not sure why it''s doing that, but it is. Any ideas? For the time being I just changed line

Hello, I'm an absolute beginner with R. I'm hoping to do some time-series analysis on my data. The data looks like #time value 18 153 20 426 70 7 83 130 84 7 and so on where time could be in seconds or hours or days (not all at the same time). How could I import such a file to R and do some simple stuff (say plot the values)? As per the tutorials on time series, I could use the ts()