similar to: question about order selection of ar

Hi there, we are beginners in R and we are trying to fit the following time series using ar(2): > x <- c(1.89, 2.46, 3.23, 3.95, 4.56, 5.07, 5.62, 6.16, 6.26, 6.56, 6.98, > 7.36, 7.53, 7.84, 8.09) The reason of choosing the present time series is that the we have previously calculated analitically the autoregressive coefficients using the direct inversion method as 1.1, 0.765, 0.1173.

Hi useRs, I'm trying to fit a basic AR(2) model with the 'ar' function. And when I try to check the value of the coefficients, I could not find the same value as the 'ar' function. Here is my example: myserie <- c(212, 205, 210, 213, 217, 222, 216, 218, 220, 212, 215, 236) #plot(myserie, type="l") myserieminus0 <- tail(myserie, -2) myserieminus1 <-

Hi useRs, I'm trying to fit a basic AR(2) model with the 'ar' function. And when I try to check the value of the coefficients, I could not find the same value as the 'ar' function. Here is my example: myserie <- c(212, 205, 210, 213, 217, 222, 216, 218, 220, 212, 215, 236) #plot(myserie, type="l") myserieminus0 <- tail(myserie, -2) myserieminus1 <-

Hi, I'm slowly working through Tsay's "Analysis of Financial Time Series" 3rd ed. ?I'm trying to replicate Table 2.1 on p.47, which gives PACF, AIC, and BIC for the monthly simple returns of the CRSP value-weighted index. The data: http://faculty.chicagobooth.edu/ruey.tsay/teaching/fts3/m-ibm3dx2608.txt > da <-

Hi everyone I've got a problem regarding the arima() and the ar() function for autoregressive series. I would simply like to combine them. To better understand my question, I first show you how I'm using these two functions individually (see file in the attachement). 1) apply(TSX,2, function(x) ar(na.omit(x),method="mle")$order # this function finds the optimal

Time Series functions in R ========================== I think a good basic S-like functionality for library(ts) in base R would include ts class, tsp, is.ts, as.ts plot methods start end window frequency cycle deltat lag diff aggregate filter spectrum, spec.pgram, spec.taper, cumulative periodogram, spec.ar? ar -- at least univariate by Yule-Walker arima -- sim, filter, mle, diag, forecast

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

Full_Name: Ian McLeod Version: 2.3.1 OS: Windows Submission from: (NULL) (129.100.76.136) > There is a simple bug in acf as shown below: > > z <- 1 > acf(z,lag.max=1,plot=FALSE) > Error in acf(z, lag.max = 1, plot = FALSE) : > 'lag.max' must be at least 1 > This is certainly a bug. There are two problems: (i) the error message is wrong since lag.max is

--- On Mon, 1/17/11, Raymond Wong <raywong365@yahoo.ca> wrote: From: Raymond Wong <raywong365@yahoo.ca> Subject: Re: [R] help in calculating ar on ranked vector To: "Uwe Ligges" <ligges@statistik.tu-dortmund.de> Received: Monday, January 17, 2011, 11:56 AM Thanks Uwe:   Here is my code. the first set of print statements work, but not the second.   #

Dear helpers, When I use ar to fit the data with length 180, I have the following error: ar(x,method="burg") Error in acf(x, type = "covariance",lag.max=order,plot=FALSE): lag.max must be at least 1 If I use ar(x), then I have Call (x=x) order selected 0 sigma^2 estimated as 5374 Obviously I missed some points for using ar. This is R 1.7.0 under Redhat Linux

Dear all R users, I am really struggling to determine the most appropriate lag order of ARIMA model. My understanding is that, as for MA [q] model the auto correlation coeff vanishes after q lag, it says the MA order of a ARIMA model, and for a AR[p] model partial autocorrelation vanishes after p lags it helps to determine the AR lag. And most appropriate model choosed by this argument gives

h?, I am preparing undergraduate thesis If you help me this would make me feel good. First I need to analyze effect of Dow Jones Industrial average(DJIA)'s return on Istanbul Stock Exchange(ISE). I want to use Markov-Switching Bayesian Vector Autoregression Models (MSBVAR) that is used to examine the effect of a large economy?s stock exchange movement on a small economy?s stock exchange

Dear R-users, I used lm() to fit a standard linear regression model to a given data set, which led to a coefficient of determination (R^2) of about 0.96. After checking the residuals I realized that they follow an autoregressive process (AR) of order 1 (and therefore contradicting the i.i.d. assumption of the regression model). I then used gls() [library nlme] to fit a linear

Dear R People: Here is some output from AR and ARIMA functions: > xb <- arima.sim(n=120,model=list(ar=0.85)) > xb.ar <- ar(xb) > xb.ar Call: ar(x = xb) Coefficients: 1 0.6642 Order selected 1 sigma^2 estimated as 1.094 > xb.arima <- arima(xb,order=c(1,0,0),include.mean=FALSE) > xb.arima Call: arima(x = xb, order = c(1, 0, 0), include.mean = FALSE)

There is now a preliminary version of a time series package in the R-devel snapshots, and we would welcome feedback on it. It is based in part on the packages bats (Martyn Plummer) and tseries (Adrian Trapletti) and in part on code I had or have written. (Thanks for the contributions, Martyn and Adrian!) Some of the existing ts code has been changed, for example to plot multiple time series, so

Hello: I have some trouble making a prediction from an AR(p) model. After I have the AR(p) model fitted , I want to use a new data set to make predictions. But I get the error: Error in newdata - object$x.mean : non-numeric argument to binary operator. A small version of my original data looks like: X1 X2 X3 X4 40813.65 1 10 41.86755 40813.65 1 8 41.86755 40813.66 1 8 41.86755

I was wondering if anyone could help with choosing optimal lag length for ZA test. There have been two lag order selection methods commonly used in the literature: 1) The ZA paper recommends to run the test with maximum number of lags. Then the lag order is reduced sequentially until the longest lag is statistically significant; 2) One could also use AIC or SBC or other criteria to choose lag

Hello, we've been more than happy with Samba 3.0.22 on our Solaris 9 machines, but when we upgraded to Solaris 10 users are experiencing a multitude of XP desktop problems: icons disappear, start menu will hang because a few items link back to a samba share, many XP windows write delay problems, the whole desktop will hang. It seems the samba server will stop responding. Is there anybody out

Hello, I have a dataset with 4 variables, each consisting of a vector, all with the same length. I start by interpolating the first three variables using the function "interp", and plot the interpolation successfully using "filled.contour". I then interpolate the first two variables and a fourth using "interp" again, but when I try to overlay the contour lines

Hello, We use LDAP to store our Maildir++ quota information for our Maildir mailboxes. I notice in the documentation that only SQL and flat files are supported by the dictionary quota if I want to use quota with mdbox? Are there any plans to allow LDAP to be used as the store? Regards, Matthew. -- Dr Matthew Williams MEng PhD MBCS Systems Administrator - IT Services - Bangor