similar to: Degrees of freedom in the Ljung-Box test

Displaying 20 results from an estimated 2000 matches similar to: "Degrees of freedom in the Ljung-Box test"

2012 Jun 26
2
Ljung-Box test (Box.test)
I fit a simple linear model y = bX to a data set today, and that produced 24 residuals (I have 24 data points, one for each year from 1984-2007). I would like to test the time-independence of the residuals of my model, and I was recommended by my supervisor to use the Ljung-Box test. The Box.test function in R takes 4 arguments:  x a numeric vector or univariate time series. lag the statistic
2008 May 16
2
Box.test degrees of freedom
Dear colleagues, I am new to R and statistics so please keep that in mind. I have doubts on the df calculation of Ljung-Box test (Box.test). The function seems to use always the df=lag=m and not df=m-p-q like suggested in Ljung and Box (1978) paper (that is referenced). Do you agree with this? If so, is there an R package function that computes Ljung-Box test with the degrees of
2011 Feb 25
0
time series with NA - acf - tsdiag - Ljung-Box
Hi all, I am modelling a time series with missing data. *Q1)* However, I am not sure if I should use the next *graphics* to understand my data: *a)* ACF & PACF (original series) *b)* ACF & PACF (residuals) * * *Q2)* I am using *tsdiag*, so I obtain a graphic with 3 plots: stand. residuals vs time; acf for residuals; Ljung-Box for residuals (it is wrong for residuals). I know that using
2006 Mar 08
1
Degrees of freedom using Box.test()
After an RSiteSeach("Box.test") I found some discussion regarding the degrees of freedom in the computation of the Ljung-Box test using Box.test(), but did not find any posting about the proper degrees of freedom. Box.test() uses "lag=number" as the degrees of freedom. However, I believe the correct degrees of freedom should be "number-p-q" where p and q are
2004 Apr 17
3
Box-Ljung p-value -> Test for Independence
Hi all I'm using the Box-Ljung test (from within R) to test if a time-series in independently distributed. 2 questions: 1) p-value returned by Box-Ljung: IF I want to test if the time-series is independant at say 0.05 sig-level (it means that prob of erroneously accepting that the time-series is independent is 0.05 right?) --> then do I consider time-series as "independant"
2019 Jun 04
0
tsdiag should pass the fitdf parameter to Box.test
Dear Everyone, The document of `tsdiag? says > These tests are sometimes applied to the residuals from an ARMA(p, q) fit, in which case the references suggest a better approximation to the null-hypothesis distribution is obtained by setting fitdf = p+q, provided of course that lag > fitdf. This implies that we should pass the `fitdf' parameter when applying `Box.test' to
2007 Apr 25
1
Box Ljung Statistics
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
2006 May 17
1
can Box test the Ljung Box test say which ARIMA model is better?
two ARIMA models, both have several bars signicant in ACF and PACF plots of their residuals, but when run Ljung Box tests, both don't show any significant correlations... however, one model has p-value that is larger than the other model, based on the p-values, can I say the model with larger p-values should be better than the model with smaller p-values? [[alternative HTML version
2009 Mar 31
1
Jarque-Bera test and Ljung-Box test for multivariate time series
Hi! I know that there is function in fBasics package for univariate Jarque-Bera test and a funtion for univariate Ljung-Box test in stats package. But I am wondering if there is a function somewhere to do the tests for multivariate time series? Thanks, John [[alternative HTML version deleted]]
2006 Feb 15
1
question about the results given by the Box.test?
Hello, I am using the Ljung Box test in R to compute if the resiudals of my fitted model is random or not. I am not sure though what the results mean, I have looked at various sources on the internet and have come up with contrasting explanations (mainly because these info deal with different program languages, like SAS, SPSS, etc). I know that my residuals should appropriate white noise( is
2009 Jul 29
0
Determination of lag value for Box.test
Hi, I saw that tsdiag function doesn't provide a correct result for Ljung-Box test. I want to use Box.test function for this, but I don't know how to determine lag parameter for this function. For fitdf, as I'm using a SARIMA model (0,1,1)(0,1,1)12, I decided to set it to 2. Can you confirm me the value for fitdf and give me a way to determine the lag value? Thanks Myriam -- View
2009 Feb 24
1
Box.test reference correction (PR#13554)
Full_Name: Peter Solymos Version: 2.8.1 OS: Windows Submission from: (NULL) (129.128.141.92) The help page of the Box.test function (stats) states that the Ljung-Box test was published in: Ljung, G. M. and Box, G. E. P. (1978), On a measure of lack of fit in time series models. Biometrika 65, 553--564. The page numbers are incorrect. The correct citation should be as follows: Ljung, G. M.
2011 Oct 05
2
creating a loop for a function
Dear All, I want to create a loop within a function r. The example follows: Box.test (lfut, lag = 1, type="Ljung") if i want to compute the Box.test for lag 1 to 10, I have to write manually change each time for different lag. So i wan to write a loop for the lag 1 to 10 and return the statistics for each lag. Is there any method to do this ? With regards, Upananda -- You may
2004 Jan 13
3
How can I test if a not independently and not identically distributed time series residuals' are uncorrelated ?
I'm analizing the Argentina stock market (merv) I download the data from yahoo library(tseries) Argentina <- get.hist.quote(instrument="^MERV","1996-10-08","2003-11-03", quote="Close") merv <- na.remove(log(Argentina)) I made the Augmented Dickey-Fuller test to analyse if merv have unit root: adf.test(merv,k=13) Dickey-Fuller = -1.4645,
2007 Dec 08
2
time series tests
Hi all, Can anyone clear my doubts about what conclusions to take with the following what puts of some time series tests: > adf.test(melbmax) Augmented Dickey-Fuller Test data: melbmax Dickey-Fuller = -5.4075, Lag order = 15, p-value = 0.01 alternative hypothesis: stationary Warning message: p-value smaller than printed p-value in: adf.test(melbmax)
2005 Jul 07
1
spurious regression in R
Hi: I am trying to do a spurious regression in R but I can not find the function. Anybody used it before? The problem I have is try to do a regression with several time series. An alternative is to use the GLS function to fit the linear regression with the correlation structure AR(3) for the response (or residual). I hope the residuals after the GLS regression will be independent judged by
2011 Jul 13
1
AR-GARCH with additional variable - estimation problem
Dear list members, I am trying to estimate parameters of the AR(1)-GARCH(1,1) model. I have one additional dummy variable for the AR(1) part. First I wanted to do it using garchFit function (everything would be then estimated in one step) however in the fGarch library I didn't find a way to include an additional variable. That would be the formula but, as said, I think it is impossible to add
2010 Jul 22
1
tsdiag
HI list, I want to know whether tsdiag uses k-(p+q) as the lag in ljung box test. How is it possible to save those values nuncio -- Nuncio.M Research Scientist National Center for Antarctic and Ocean research Head land Sada Vasco da Gamma Goa-403804 [[alternative HTML version deleted]]
2009 May 20
1
stationarity tests
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
2011 Sep 27
4
Question concerning Box.test
Hi everyone, I've got a question concerning the function Box.test for testing autocorrelation in my data. My data consist of (daily) returns of several stocks over time (first row=time, all other rows=stock returns). I intend to perform a Box-Ljung test for my returns (for each stock). Since I have about 3000 stocks in my list, I'm not able to perform the test individually for each