similar to: acf () and pacf()

Hi, I am pretty new to rsync so this question might have a very trivial answer. Sorry for that then. (using google didn't work though) I want to synchronise the files from my laptop to my machine at work and back from time to time. Both machines have linux (the laptop has fedora core 2 with a 2.6.6 kernel and the remote machine redhat 9 with a 2.6.3 kernel) On the laptop I use rsync

Hi, I wanted to understand exactly how acf and pacf works, so I tried to calculate ac and pac manually. For ac, I used the standard acf formula: acf(k) = sum(X(t)-Xbar)(X(t-k)-Xbar))/sum(X(t)-Xbar)^2. But for pac, I could not figure out how to calculate it by hand. I understand that in both R and EVIEWS, it is done using the Durbin-Levinson algorithm by the computer. However, I don't

Hi, I noticed that whenever I ran acf or pacf, the plot generated by R always includes two horizontal blue doted lines. Furthermore, these two lines are not documented in the acf documentation. I don't know what they are for, but it seems that they are important. Could someone tell me what they are and how are they calculated? Thanks, -- Tom [[alternative HTML version deleted]]

Hi helpers, can you help me in plotting acf and pacf functions in R. I am using the code acf(variable name) but it is not working. Expecting your reply. Thanks -- View this message in context: http://n4.nabble.com/ACF-and-PACF-tp1477149p1477149.html Sent from the R help mailing list archive at Nabble.com.

I have data as below.Please let me know how the ACF and Pacf used to determine the order od arima model. Is there any rules need to be followed to determine order.Please advise > turkey.price.ts Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2001 1.58 1.75 1.63 1.45 1.56 2.07 1.81 1.74 1.54 1.45 0.57 1.15 2002 1.50 1.66 1.34 1.67 1.81 1.60 1.70 1.87 1.47 1.59 0.74 0.82

I am getting the following: *** Weave Errors *** Error in driver$runcode(drobj, chunk, chunkopts) : Error in eval(expr, envir, enclos) : couldn't find function "pacf.mts" *** Source Errors *** Error in eval(expr, envir, enclos) : couldn't find function "pacf.mts" make[1]: *** [checkVignettes] Error 1 I don't really understand the new namespace mechanism,

pacf in devel seems by default to return a different number of lags than 1.7.1 for $pacf. I don't see any mention of this in the NEWS file, or any change in the documentation, so I suspect it is and error, though it may be an undocumented improvement. (Newbie question: How is the simplest way to display a function like pacf.default that is not exported from a namespace?) Paul

Dear all, following the thread http://tolstoy.newcastle.edu.au/R/e2/devel/07/09/4338.html regarding the bug in the partial autocorrelation function for multivariate time series. I have prepared a web page with patches and relevant information. http://www2.stat.unibo.it/giannerini/R/pacf.htm Please do not hesitate to contact me for further clarifications regards Simone --

R: Is there an easy way to get the acf and pacf for an irregular times series? That is, the acf and pacf with lag lengths that are in units of time, not observation number. Thanks, Jason Higbee Research Associate Federal Reserve Bank of St. Louis The views expressed in this email are the author's and not necessarily those of the Federal Reserve Bank of St. Louis or the Federal Reserve

Hello Michael, see as an online resource: http://www.statsoft.com/textbook/sttimser.html or get hold on a time series analysis textbook, like one of the monographies written by Hamilton; Luetkepohl; Brockwell & Davis; Harvey or Box & Jenkins, to name but a few. In a nutshell, PACF 'eliminates' intermediate autocorrelations compared to ACF, e.g. an AR(1) process will ordinarily

When I use the command for PACF, lags 5, 10, 15, and 20 are labeled. I would like to label lag 1. I would greatly appreciate if someone could tell me how to do this. Below is the command that I am using: pacf(data$R1,main="Series R1 Residuals") [[alternative HTML version deleted]]

I have asked this question on Stackoverflow and was told it does not relate to the sites' mission as it is statistical question, thus I brought it here. I am fitting a gam mode in the mgcv package to study associations of environmental pollutants and mortality. The aim is to choose a model with lowest mgcv and also to reduce the PACF to less than < |0.1|. library(gamair) library(mgcv)

Dear all, following the thread http://tolstoy.newcastle.edu.au/R/e2/devel/07/09/4338.html regarding the bug in the partial autocorrelation function for multivariate time series. I have prepared a web page with patches and relevant information. http://www2.stat.unibo.it/giannerini/R/pacf.htm Please do not hesitate to contact me for further clarifications regards Simone --

Dear list, according to the documentation of acf{ts} "the partial correlation coefficient is estimated by fitting autoregressive models of successively higher orders up to lag.max. " However, R seems to return the Yule-Walker estimates of the PACF by default. You can check this using c(1:10) as the series: the YW estimates are 0.7000000 and -0.1527035 for lags 1 and 2 . If the PACF

dear sir, i want to use wine in my linux 7.0 redhat. the problem i face is that when i try to install the wine product. the installer ask me for libfreetype.so.6 libraries as dependancies. which i don't have. where can i get these libraries from. tell me the url. i shall be very great full to you. thanx.. khawar ameer malik __________________________________________________ Do You

Dear Ivo, dear list, (see: Message: 70 Date: Thu, 26 Mar 2009 21:39:19 +0000 From: ivowel at gmail.com Subject: [R] pgmm (Blundell-Bond) sample needed) I think I finally figured out how to replicate your supersimple GMM example with pgmm() so as to get the very same results as Stata. Having no other regressors in the formula initially drove me crazy. This was a case where simpler models are

Hi All R Experts, I met with below mentioned statistics in paper "Stock Index Volatility Forecasting with High Frequency Data" by Eugenie Hol, Siem Jan Koopman http://ideas.repec.org/p/dgr/uvatin/20020068.html I would like to ask that what is "Box-Ljung portmantacau statistic based on N squared autocorrelation" ? Is it same as "Box-Ljung Statistics" of stats

Hi I found on google that there is an implementation of hot-deck imputation in SAS: http://ideas.repec.org/c/boc/bocode/s366901.html Is there anything similar in R? Many Thanks Eleni Rapsomaniki

I am interested in comparing the fit of robust (i.e., S and MM) and non-robust (i.e., OLS) estimators when applied to a particular data set. The paper entitled "A comparison of robust versions of the AIC based on M, S and MM-estimators" (available at: http://ideas.repec.org/p/ner/leuven/urnhdl123456789-274771.html) presents formulas for robust Akaike information criteria (AIC) for the M,

Dear Carlos, please refrain from posting the same question umpteen times. Please consider that code is hard to read and people might not have the time to run your simulation etc. etc.. As I told you privately in response to your message on 18/1, > Re: generating correlated effects, I tried this only once, but I > didn't get it right. Simulations using this are, e.g., Hansen (2007)