similar to: AR vs ARMA model

How to compute the p-value of a statistic generally? -- View this message in context: http://r.789695.n4.nabble.com/p-value-tp2217867p2217867.html Sent from the R help mailing list archive at Nabble.com.

Hello, I would like to compute ARMA and AR using arima-function in R. My question is: If I have Null=zero values in my data, what should I do? Remove ? or doesn't matter for ARIMA-models and I can estimate my coefficients including zero values in data in arima-function in R ? What is the better way? How to manage the data for ARIMA estimation? Thank you. [[alternative HTML version

Hello I am facing a curious problem.I have a time series data with which i want to fit auto-regressive model of order p, where p runs from 1:9.I am using a for loop which will fit an AR(p) model for each value of p using the *ar.ols* function. I am using the following code for ( p in 1:9){ a=ar.ols (x=data.ts, order.max=p, demean=T, intercept=T) } Specifying the *order.max* to be p, it gives me a

Hi, I need a function to convert an ARMA process to an "infinite" AR process. I know that in the Stats package exist one to convert an ARMA to MA, but i can't find one function to convert to AR. There exists one? THANKS

Hi, Let theta be the coefficient in AR(1) model, the components of the correlation structure is equal to 1 for times s = t, and theta^|t-s| for t > s. Could someone do me a favour to give some ideas on the correlation structure in AR(2) model and correlation structure of ARMA(p,q), as well? Thank you Fir [[alternative HTML version deleted]]

(My apologies if this is a repeated posting. I couldn't find any trace of my previous attempt in the archive.) I'm having trouble with forecast() in the dse2 package. It works fine for me on a model without a trend, but gives me NaN output for the forecast values when using a model with a trend. An example: # Set inputs and outputs for the ARMA model fit and test periods

I'd like to fit an ARMA(1,1) model to some data (Federal Reserve Bank interest rates) that looks like: ... 30JUN2006, 5.05 03JUL2006, 5.25 04JUL2006, N <---- here! 05JUL2006, 5.25 ... One problem is that holidays have that "N" for their data. As a test, I tried fitting ARMA(1,1) with and without the holidays deleted. In other words, I fit the above data

Hi there, Does anyone know how to predict ARMA? It doesn?t have either predict or forecast methods. I found couple of packages called fbasic and fseries at http://www.itp.phys.ethz.ch/econophysics/R/, which has ?arma.predict? in it, but it doesn?t seem to be working. Any help in this regard would be appreciated. Thanks in advance. Regards Skanda Kallur "Prediction is very difficult,

Hello,Could somebody tell me what is the difference between  theese 3 calls of functionsarma(x,order=c(1,0)), arima(x,order=c(1,0,0)) ar(x,order=1)?I expected same residuals of theese three models,but unexpectably for the first two R requiredinitial value of something (what?)...Thanks in advance!  [[alternative HTML version deleted]]

Hi, I want to fit a regression model with one independent variable. The error part should be fitted an ARMA process. For example, y_t = a + b*x_t + e_t where e_t is modelled as an ARMA process. Please let me know how do I do this in R. What code should I use? TIA Aditya [[alternative HTML version deleted]]

Hello, The "arma" function in the "tseries" package allows estimation of models with specific "ar" and "ma" lags with its "lag" argument. For example: y[t] = a[0] + a[1]y[t-3] +b[1]e[t-2] + e[t] can be estimated with the following specification : arma(y, lag=list(ar=3,ma=2)). Is this possible with the "arima" function in the

In the summary of the output of arma, there's a number Pr(>|t|), however, I don't know what is its meaning - at least, it doesn't _seem_ to be a Student's t distribution. Reproducible test case: x <- c(0.5, sin(1:9)) reg <- arma(x, c(1,0)) summary(reg) <output> Call: arma(x = x, order = c(1, 0)) Model: ARMA(1,0) Residuals: Min 1Q Median 3Q

Dear R users, I need to fit an ARMA model. As far as I've seen, EACF (extended ACF) is not available in R. 1. Let's say I fit a series of ARMA models in a loop. Given the code/output included below, how do I pull 'Model' and 'Fit' (AIC) from each summary() so that I can combine them into an array/data frame to be sorted by AIC? 2. Apart from EACF, are you aware perhaps

Dear all R user, Please forgive me if my problem is too simple. Actually my problem is basically Statistical rather directly R related. Suppose I have return series ret with mean zero. And I want to fit a Garch(1,1) on this. my is r[t] = h[i]*z[t] h[t] = w + alpha*r[t-1]^2 + beta*h[t-1] I want to estimate the three parameters here; the R syntax is as follows: #

Dear R experts, I am trying to estimate an ARMA 2,2 model with garch errors. I used the following code on R 2.9. #library library(fGarch) #data data1<-ts(read.table("C:/Users/falcon/Desktop/Time Series/exports/goods1.csv"), start=c(1992,1), frequency=12) head(data1) #garch garchFit(formula.mean= ~arma(2,2),formula.var=~garch(1,1), data=data1) but get this error: >

Hello - Here's what I'm trying to do. I want to fit a time series y with ARMA(1,1) + GARCH(1,1), there are also an exogeneous variable x which I wish to include, so the whole equation looks like: y_t - \phi y_{t-1} = \sigma_t \epsilon_t + \theta \sigma_{t-1} \epsilon_{t-1} + c x_t where \epsilon_t are i.i.d. random variables \sigma_t^2 = omega + \alpha \sigma_{t-1}^2 + \beta

Dear List, I am new to TS-Modeling in R. I would like to fit an ARMA(1,1) model for a balanced panel, running Y on a full set of unit and year dummies using an arma(1,1) for the disturbance: y_it=unit.dummies+yeardummies+e_it where: e_it=d*e_it-1+u_it+q*u_it-1 How can I fit this model in R? arma() does not seem to take covariates (or I don't understand how to specify the function so that

Hi all, Suppose I am fitting an arma(p,q) model to a time series y_t. So, my model should contain (q+1) white noise variables. As far as I know, each of them should have the same variance. How do I get the estimate of this variance by running the arma(y) function (or is there any other way)? Appreciate your help. Thanks, Preetam -- Preetam Pal (+91)-9432212774 M-Stat 2nd Year,

> Cordial saludos a tod en s. > > Estoy leyendo un tema y tengo la siguiente necesidad. > > Los contacto para pedirles MUY ENCARECIDAMENTE ME AYUDEN con la > explicación DE CÓMO HACER EL MODELO ARMA en R DE UNA SEÑAL CUALQUIERA para > obtener de ella el modelo matemático fraccional aproximado, esto para > obtener el PSD de la señal (Power Density Spectrum). > > La

R-guRus , ARMA function in tseries, seems to be calculating the AR coeff 's as coef <- lm(xx[,1]~xx[,lag$ar+1])$coef [*snipped* from around line 77,] I'd like to modify this model with another term somewhat in these lines lm(xx[,1] ~xx[,lag$ar+1]+mvgsignal)$coef where mvgsignal is a moving average signal based on some indicators, the question is could i simply hack into