similar to: Partial whitening of time series?

Displaying 20 results from an estimated 6000 matches similar to: "Partial whitening of time series?"

2002 Oct 10
4
Generating AR1 data
Hi, Is there an easy way to generate data with temporal autocorrelation? I want to generate data with something like rnorm where I can specify the mean, variance and time lag. Does such a thing exist? Yours, AB -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",
2011 Jun 30
0
CCF of two time series pre-whitened using ARIMA
Hi all, I have two time series that I would like to correlate but as they are autocorrelated, I am "pre-whitening" them first by fitting ARIMA models, then correlating their residuals....as described in https://onlinecourses.science.psu.edu/stat510/?q=node/75 However, http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm discusses some issues with ARIMA in R. In particular, for issue 2, if
2011 Sep 09
1
Exception in NeweyWest - Pre-Whitening necessary?
Hi guyz, I have run my algorithm in R (see http://pastebin.com/q84Tujfg) and got the following error: Error in ar.ols(x, aic = aic, order.max = order.max, na.action = na.action, : 'order.max' must be < 'n.used' I am pretty sure, that the error comes from the NeweyWest function in line 45, as the NeweyWest function uses the ar.ols() function for pre whitening. Does anyone
2009 Feb 16
2
Whitening Time Series
Hi R users, I am doing cross correlation analysis on 2 time series (call them y-series and x-series) where I need the use the model developed on the x-series to prewhiten the yseries.. Can someone point me to a function/filter in R that would allow me to do that? Thanks in advance for any help! -- View this message in context:
2002 Nov 26
1
floor curve question (whitening filter)
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN"> <HEAD><META http-equiv=Content-Type content="text/html; charset=iso-8859-1"></HEAD> <BODY bgColor=#ffffff><FONT face="verdana,arial" size="2"> Hi there,</P> one step in the encoding process (if I got it right), would becomputing a "floor
2002 Jul 30
1
Comparison of two time series using R
We have two time series: the first is a series of weekly counts of isolates of RSV (respiratory syncytial virus) by pathology laboratories, and the second is a series of weekly counts of cases of bronchiolitis in young children presenting to hospital emergency departments. Bronchiolitis in young children is usually caused by RSV infection, and simple visual inspection reveals a very close
2007 May 14
1
Free Colgate Max Fresh Whitening Toothpaste
http://www.colgate.toothpaste-sample.com Get New Colgate Max Fresh Whitening Toothpaste. Cool Mint Flaor with Breath Strips. -- Posted via http://www.ruby-forum.com/. --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Ruby on Rails: Talk" group. To post to this group, send email to
2003 Jan 06
2
Removing autocorrelations
Could anyone tell me whether there is an R function for removing autocorrelations from a series of observations before performing a linear or nonlinear regression analysis on them? Many thanks, Andrew Wilson
2011 Mar 16
1
Autocorrelation in linear models
I have been reading about autocorrelation in linear models over the last couple of days, and I have to say the more I read, the more confused I get. Beyond confusion lies enlightenment, so I'm tempted to ask R-Help for guidance. Most authors are mainly worried about autocorrelation in the residuals, but some authors are also worried about autocorrelation within Y and within X vectors
2009 Aug 24
1
lme, lmer, gls, and spatial autocorrelation
Hello folks, I have some data where spatial autocorrelation seems to be a serious problem, and I'm unclear on how to deal with it in R. I've tried to do my homework - read through 'The R Book,' use the online help in R, search the internet, etc. - and I still have some unanswered questions. I'd greatly appreciate any help you could offer. The super-super short explanation is
2004 Jul 21
2
Testing autocorrelation & heteroskedasticity of residuals in ts
Hi, I'm dealing with time series. I usually use stl() to estimate trend, stagionality and residuals. I test for normality of residuals using shapiro.test(), but I can't test for autocorrelation and heteroskedasticity. Is there a way to perform Durbin-Watson test and Breusch-Pagan test (or other simalar tests) for time series? I find dwtest() and bptest() in the package lmtest, but it
2006 Feb 23
1
partial mantel test
I would like to know how to run a partial mantel test controlling for spatial autocorrelation and correlation with other environmental variables. It seems that with function included in vegan for partial mantel test I can only test for the relationship between two variables controlling for the effect of a third one. Thanks a lot Alexandra --- Lic. Alexandra Sapoznikow Centro Nacional
2004 Aug 25
1
Newbie Question: Spatial Autocorrelation with R Tutorial?
Howdy All, I am looking for some good tutorials (books, websites, whatever) for calculating/testing for Spatial Autocorrelation using R. Specifically, I am wanting to test for autocorrelation of a number of variables measured at a set of discrete locations. Up to this point I have been exploring the "spdep" package and I can get "moran.test" to work, but I am concerned that
2008 Oct 08
0
partial autocorrelation plots ACF type=p
Dear users, I have two continuous variables which are two different measures taken each year from 1975 to 2005. I want to see if the two variables are correlated but need to take into account the fact that they are a time series. I have been following an example from 'The R Book' where you plot the ACF: par(mfrow=c(1,1) acf(cbind(x,y)) and this appeared to work fine, producing four
2008 Jul 06
1
Different Autocorrelation using R and other softwares
Dear All, Would like to ask the inconsistency in the autocorrelation from R with SPSS/Minitab. I have tried a dataset x with 20 data (1-20) and ask R to give the autocorrelation of different lags using the command < acf(x, lag.max=100, type = "correlation"), However while SPSS and Minitab give the same answers (0.85 for lag1), R gives 0.3688 which is much smaller. Obviously, the
2009 Oct 06
1
Spatial Autocorrelation
Hello, I have a matrix with the distances among sites. And I have another matrix with the presence and absence of each species in each site. I would like to test the spatial autocorrelation among sites. I have tried to use the function gearymoran of the ade4 package, but error messages keep popping up. Do you know any function for me to test the spatial autocorrelation of my data? Thanks,
2010 Apr 29
1
a question on autocorrelation acf
Hi R users, where can I find the equations used by acf function to calculate autocorrelation? I think I misunderstand acf. Doesn't acf use following equation to calculate autocorrelation? [image: R(\tau) = \frac{\operatorname{E}[(X_t - \mu)(X_{t+\tau} - \mu)]}{\sigma^2}\, ,] If it does, then the autocorrelation of a sine function should give a cosine; however, the following code gives a
2005 Feb 10
2
correcting for autocorrelation in models with panel data?
Hi I have some panel data for the 50 US states over about 25 years, and I would like to test a simple model via OLS, using this data. I know how to run OLS in R, and I think I can see how to create Panel Corrected Standard Errors using http://jackman.stanford.edu/classes/350C/pcse.r What I can't figure out is how to correct for autocorrelation over time. I have found a lot of R stuff on
2007 Aug 14
1
OT - use of R
Hello, is there an up-to-date reference for how many people use R? I'm giving an R demo and want to cite wonderful R usage stats. How many people use it (or download it)? How often is R used in peer-reviewed pubs, etc. Is there any whiz-bang citation that says something like "R is great and developed by the best minds in statistical computing." Any thoughts? -Andy
2011 Nov 15
1
equal spacing of the polygons in levelplot key (lattice)
Given the example: R> (levs <- quantile(volcano,c(0,0.1,0.5,0.9,0.99,1))) 0% 10% 50% 90% 99% 100% 94 100 124 170 189 195 R> levelplot(volcano,at=levs) How can I make the key categorical with the size of the divisions equally spaced in the key? E.g., five equal size rectangles with labels at levs c(100,124,170,189,195)? Apologies if this is obvious. -A R> version