similar to: time series contains internal NAs error

How can I make sure the residual signal, after subtracting the trend extracted through some technique, is actually trend-free ? I would greatly appreciate any suggestion about some Stationarity tests. I'd like to make sure I have got the difference between ACF and PACF right. In the following I am citing some definitions. I would appreciate your thoughts. ACF(k) estimates the correlation

Hello All, I am trying to carry out variable reduction. I do not have information about the dependent variable, and have only the X variables as it were. In selecting variables I wish to keep, I have considered the following criteria. 1) Percentage of missing value in each column/variable 2) Variance of each variable, with a cut-off value. I recently came across Weka and found that there is an

Hi R users, I request members of the R community to consider filling a short survey regarding the use of R. The survey can be found at http://goo.gl/jw1ig Please accept my apologies for posting here for a non-technical reason. The data collected will be suitably analyzed and I'll post a link to the results in the coming weeks. Thank you all for your interest and for sharing your R usage

Hi, I am newbie user of ggplot and would like some assistance in implementing time series plots. I'd like to know how the tsdiag plot can be made in ggplot? Thanks Harsh Singhal Decisions Systems, Mu Sigma Inc.

Hi! I want to plot three graphs (residuals, ACF and PACF of a model). Ideally I would use a c(2,2) disposition where the residuals plot would start at position 1,1 and span to position 1,2. Then I would plot the ACF in position 2,1 and the PACF in position 2,2. Maybe is clearer like this: -------------------------- | | | residuals | |

hi, in 1.9.1, the return value from ARMAacf(pacf=TRUE) is not named by lags, contrary to ?ARMAacf. the simple fix is to move names(Acf) <- down after if(pacf), with an appropriate starting lag as pacf=TRUE appears to start at lag 1 (whereas pacf=FALSE starts at lag 0). for consistency, one could argue to append 1 for lag 0 for pacf=TRUE (or start pacf=F at lag 1). however, given the

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

An embedded and charset-unspecified text was scrubbed... Name: not available URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20091123/470946bc/attachment-0001.pl>

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

HI R users, I would appreciate information/examples/suggestions on building GUIs for R applications. I am currently working on a project that would require the following functionalities : 1) Display a window to the user. Provide a function to scan local drive and choose dataset file. 2) Display the column names for the user to choose the dependent variable and the independent variables. 3) Fit

Hi UseRs, I recently started working with the RGtk2 library. The documentation is comprehensive and I've tried learning from the examples in most Gtk tutorials (which have C code). This is a little problematic, but has helped quite a bit in getting me started. I would like to create a GUI for file selection, which then displays the column names from the selected file, and provides the user

Hi useRs, I would like to know what R users are employing to get their images/plots created in R, into Excel sheets. I am aware of the various packages (xlsReadWrite, RODBC) to get data frames into R, but I would like to copy images too. Thank you for any help in solving this problem. Regards, Harsh Singhal

I have used acf() and pacf() in R to get the acf and pacf values at max/lag=20 but the output did not show the values associated with lag numbers. lag numbers is shown in decimals. -- Rashid Ameer View my recent publication at * http://www.emeraldinsight.com/fwd.htm?id=aob&ini=aob&doi=10.1108/17538391211282854 * Details for my works are available directly at

Estimados amigos Estoy dibujando las funciones acf y pacf de una variable de una serie "zoo": > ls.str(pat="T0.5") T0.5 : 'zoo' series from 2017-11-08 23:00:00 to 2017-11-15 06:59:00   Data: num [1:9120, 1:3] 55 49.8 51 50.1 36.5 ...   Index:  POSIXct[1:9120], format: "2017-11-08 23:00:00" "2017-11-08 23:01:00" "2017-11-08

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.

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, 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

Hello useRs, I have a problem at hand which I'd think is fairly common amongst groups were R is being adopted for Analytics in place of SAS. Users would like to obtain results for logistic regression in R that they have become accustomed to in SAS. Towards this end, I was able to propose the Design package in R which contains many functions to extract the various metrics that SAS reports.

Hi All, I am trying to assemble a system that will allow me to work with large datasets (45-50 million rows, 300-400 columns) possibly amounting to 10GB + in size. I am aware that R 64 bit implementations on Linux boxes are suitable for such an exercise but I am looking for configurations that R users out there may have used in creating a high-end R system. Due to a lot of apprehensions that SAS

I'm trying to fit a SARIMA(p,d,q)x(P,D,Q) with seasonal period s to some data. When dealing with these types of models one often looks at the ACF and PACF of the time series at lags that are multiples of s, to identify potential values of P, Q. How would I do this in R given the original time series? Secondly given a time series x acf(x) just gives me the plot of the acf. How would I actually