similar to: How to get the t-stat for arima()?

Hello all, I use the arima to get a model, i.e. fit = arima(x,order=c(1,0,0)) and I know I can get the following from fit via est.coef = coef(fig) est.aic = fit$aic std.err = sqrt(diag(vcov(fit))) t.stat = est.coef/std.err How can I get the following stat from arima? Pr(>|t|) r2 adjust_r2 rmse Thanks, Rebecca

Hello, I try to look at the source code of predict() it turns out that I cannot find it. I can see it with debug(library), but not efficient. Can someone help? Thanks, Rebecca ---------------------------------------------------------------------- This message, and any attachments, is for the intended r...{{dropped:5}}

Hi R-users, I am using arima to fit a time series. Now I would like to include an intervention component "It (0 before intervention, 1 after)" using different types of impacts, that is, not only trying the simple abrupt permanent impact (yt = w It ) with the xreg option but also trying with a gradual permanent impact (yt= d * yt-1 + w * It ), following the filosophy of Box and Tiao

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

Hi all, I?m using the arima() function to study a time series but it gives me the following error: Error en optim(init[mask], armafn, method = "BFGS", hessian = TRUE, control = optim.control, : non-finite finite-difference value [3] I know that I can change the method of the arima() to "CSS" instead of "ML" but I'm specially interested in using

It works!!! Thank you so much for your help! Sent from my iPhone > On Feb 3, 2020, at 3:47 AM, Rui Barradas <ruipbarradas at sapo.pt> wrote: > > ?Hello, > > You can solve the problem in two different ways. > > 1. Redefine storage1 as a matrix and extract the aic *in* the loop. > > storage1 <- matrix(0, 4, 4) > for(p in 0:3){ > for(q in 0:3){ >

Hello I am trying to extract AICs from an ARIMA estimation with different combinations of p & q ( p =0,1,2,3 and q=0,1.2,3). I have tried using the following code unsucessfully. Can anyone help? code: storage1 <- numeric(16) for (p in 0:3){ ? ? for (q in 0:3){ ? ? ? storage1[p]? <- arima(x,order=c(p,0,q), method="ML")} } storage1$aic [[alternative HTML version deleted]]

I am nowaware that I should not post this type of questions on this group. However, Iwould like to have some clarifications related to the response you've?alreadyprovided. The code you provided yields accurate results, however I still haveissues grasping the loop process in case 1 & 2. In case1,?the use of?"p+1" and "q+1" is still blurry tome? Likewise "0L"

Hello, I'm an R newbie. I've tried to search, but my search skills don't seem up to finding what I need. (Maybe I don't know the correct terms?) I need the standard errors and not the confidence intervals from an ARIMA fit. I can get fits: > coef(test) ar1 ma1 intercept time(TempVector) - 1900

Hi, I'm using the function arima() from the ts package. when the function gives me the output I can see the s.e. of the coefficients. However I cannot find a way to collect them in a object estimate<-arima(x, order=c(1,0,1)) estimate$se does not work in fact str(estimate) does not contain $se. How is it possible? The function compute and print that value but it is not the resulting

Dear All, R 1.9.1, Windows When copying and pasting a few lines from the 'predict.Arima' help, I get an error message: > data(lh) > predict(arima(lh, order = c(3,0,0)), n.ahead = 12) Error in eval(expr, envir, enclos) : Object "xreg" not found On the other hand, the following is OK: > data(lh) > predict(arima0(lh, order = c(3,0,0)), n.ahead = 12) $pred Time

Hello, I do have two different time series A and B, they are different in length and starting point. A starts in Jan, 2012 and ends in Dec, 2012 and B starts in March, 2012 and ends in Nov, 2012. How can I plot those two series A and B in the same plot? I.E., from Jan. 2012 - Feb, 2012, it would have one data point from A and from Mar, 2012-Nov, 2012, it would have two data points from A and B,

Hi, Can anyone explain how the standard error in arima() is calculated? Also, how can I extract it from the Arima object? I don't see it in there. > x <- rnorm(1000) > a <- arima(x, order = c(4, 0, 0)) > a Call: arima(x = x, order = c(4, 0, 0)) Coefficients: ar1 ar2 ar3 ar4 intercept -0.0451 0.0448 0.0139 -0.0688 0.0010 s.e.

Hello, Is there a better way to use paste such as: a = paste(colnames(list.indep)[1],colnames(list.indep)[2],colnames(list.indep)[3],colnames(list.indep)[4],colnames(list.indep)[5],sep="+") > a [1] "aa+dummy1+dummy2+bb+cc" I tried a = paste(colnames(list.indep)[1:5],sep="+") > a [1] "aa" "dummy1" "dummy2"

Hi, I'm a beginner using R and I'm modeling a time series with ARIMA. I'm looking for a way to determine the p-values of the coefficients of my model. Does ARIMA function return these values? or is there a way to determine them easily? Thanks for your answer Myriam

I am using the ts package to fit ARIMA models, and the tsdiag() function to plot diagnostics. In doing so I'm generating an awful lot of diagnostic plots of different models and different data sets all within the same R session. So my question is, is there an option in tsdiag() similar to <main="Title"> that I can use? This would be quite helpful when I print out the plots,

I would like to simulate some SARIMA models, e.g. a SARIMA (1,0,1)(1,0,1)[4] process. I installed the package 'forecast', where the function simulate.Arima should do what I am trying to do. I am not able to understand how it works Could somebody help me with an example? thank you Stefano Sofia AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere informazioni

I have already fitted several models using R code; arima(rates,c(p,d,q))  As I heard, best model produce the smallest AIC value, but maximum likelihood estimation procedure optimizer should converge. How to check whether maximum likelihood estimation procedure optimizer has converged or not? [[alternative HTML version deleted]]

Hello, How can I judge if a string is in a group of string? For example, I would like to have if (subpool in pool){ }else{ } Where > pool = c("s1","s2") > subpool = c("s1") How can I write the "subpool in pool" right in R? Thanks very much! Cheers, Rebecca ---------------------------------------------------------------------- This message,

Hello all, When I tried to plot the following two arrays in one figure with the following: x = c(0,0,0,10,20,30) y = c(40,50,60,70,80,90) plot(x, type='o', ylim=c(min(x),max(x))) par(new=T) plot(y, type='l', ylim=c(min(y),max(y))) Found that the first points and last points from those two arrays are overlapping together, but the value 30 is not equal to 90. How could I draw