similar to: Prediction errors from forecast()?

Hello everybody! I have a problem when I try to perform a forecast of an ARIMA model produced by an auto.arima function. Here is what I'm doing: c<-auto.arima(fil[[1]],start.p=0,start.q=0,start.P=0,start.Q=0,stepwise=TRUE,stationary=FALSE,trace=TRUE) # fil[[1]] is time series of monthly data ARIMA(0,0,0)(0,1,0)[12] with drift : 1725.272 ARIMA(0,0,0)(0,1,0)[12] with drift

Hello R users, Hope everyone is doing great. I have a dataset that is in .csv format and consists of two columns: one named Period (which contains dates in the format yyyy_mm) and goes from 1995_10 to 2007_09 and the second column named pcumsdry which is a volumetric measure and has been formatted as numeric without any commas or decimals. I imported the dataset as pauldataset and made use of

Hello everybody! I have an ARIMA model for a time series. This model was obtained through an auto.arima function. The resulting model is a ARIMA(2,1,4)(2,0,1)[12] with drift (my time series has monthly data). Then I perform a 12-step ahead forecast to the cited model... so far so good... but when I look the plot of my forecast I see that the result is really far from the behavior of my time

Dear R-helpers, I would appreicate if someone can help me on the transfer parameter in ARIMAX and also see what I am doing is correct. I am using ARIMAX with 2 Exogeneous Variables and 10 years data are as follows: DepVar Period, depVar, IndepVar1 Period, indepVar1, IndepVar2 Period, indepVar2 Jan 1998,708,Jan 1998,495,Jan 1998,245.490 Feb 1998,670,Feb 1998,421.25,Feb 1998,288.170 Mar

hi: I am trying to fit prediction intervals for an arima object. My search led me to the link: http://finzi.psych.upenn.edu/R/library/forecast/html/forecast.Arima.html which has the function "forecast", as I wanted. However, when I try to run it in R, I get the message: Error in plot(forecast(fit)) : could not find function "forecast" Even the example provided on the page

Dear all, I'm new to R and time series analysis. I'd appreciate if you could shed light on my problem. Here is what I have been trying to do: 1. I fit the model ARIMA(1,0,0) with the training dataset xdata[1:100] fitit = arima(xdata, order=c(1,0,0) 2. I have some current observations in the buffer. Say that buf = xdata_new[1:20] 3. I'm trying to forecast the xdata_new[21] based on

Hi all,,Im using function arima() I.e series is my data model<-arima(series,c(1,0,0)) forecast<-predict(model,80) I want to create a variable: b1<-forecast$pred - 1.96*forecast$se and save in a txt file but using this: save(b1, file= "b1.txt") creates afile butwith this inside: ]{HQ ~|LJIiW*-l)% )m#), RIiSfdbGur9p94; H"L#Rez 1y3pN8{,I6W!6= {6l?OMw_5KZ+ =

Hello R users, I want to export to an xls or .csv some predictions I produced with the auto.arima and forecast functions. A detail of all my work is presented below. I loaded a package called dataframes2xls and tried to use the function write.xls without any success. Can anybody help me figure this out? How could I get R to export the output to an xls file? Any help will be greatly

Hello, I have a question regarding the predict command for ARIMA models. Why do I not have to give any input except the number of steps for the forecast? Which input value is used (in my case for “y(t)”)? Will the last parameter of the estimate vector be used (in my example “6”)? x <- c(1,2,3,4,5,6)model <- arima(x, order=c(1,0,0), method="ML")predict(model, n.ahead = 1) ->

Dear all, I stumbled upon what appears to be a troublesome issue when sampling from an ARIMA model (from Rob Hyndman's excellent 'forecast' package) that contains a seasonal AR component. Here's how to reproduce the issue. (I'm using R 2.9.2 with forecast 2.19; see sessionInfo() below). First some data: > x <- c( 0.132475, 0.143119, 0.108104, 0.247291, 0.029510,

Hello All, I trying to use the function auto.arima(....) from package forecast but I have a problem. My steps after I used the function auto.arima(...) I create the time series like this: >bbrass = scan("C:/Program Files/R/data PTIN/my_file.dat") >regts.start = ISOdatetime(2006, 7, 1, hour=0, min=0, sec=0, tz="GMT") #2006 07 01 00 >regts.end = ISOdatetime(2006, 7,

Hi, I have been using this website ( http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm ) to help me to fit ARIMA models to my data. At the moment I have two possible methods to use. Method 1 If I use arima(ts.data, order=c(1,2,0), xreg=1:length(ts.data)) then the wrong value for the intercept/mean is given (checked on SPSS and Minitab) and

I have been trying to simulate from a time series with trend but I don't see how to include the trend in the arima.sim() call. The following code illustrates the problem: # Begin demonstration program x <- c(0.168766559, 0.186874000, 0.156710548, 0.151809531, 0.144638812, 0.142106888, 0.140961714, 0.134054659, 0.138722419, 0.134037018, 0.122829846, 0.120188714,

Hi, I've fitted a GARCH(1,1) for the residuals of my time serie (X). X is an ARMA(1,1) process. Now I want to do a n-step forecast for X, knowing these processes. How can I do this? I know that there's a command: predict() for ARIMA processes and so on, but what about GARCH? I've got: arma=arima(x, order=c(1,0,1)) (...) garch11<-garch(residuals(x),order = c(1, 1))

Hello, In order to do a future forecast based on my past Time Series data sets (salespricesproduct1, salespricesproduct2, etc..), I used arima() functions with different parameter combinations which give the smallest AIC. I also used auto.arima() which finds the parameters with the smallest AICs. But unfortuanetly I could not get satisfactory forecast() results, even sometimes catastrophic

Hello everyone, I'm doing some benchmark comparing Arima [1] and SVR on time series data. I'm using an out-of-sample one-step-ahead prediction from Arima using the "fitted" method [2]. Do someone know how to have a two-steps-ahead forecast timeseries from Arima? Thanks, Matteo Bertini [1] http://robjhyndman.com/software/forecast [2] AirPassengers example on page 5

Hello, I have a question about forecast under model arima(1,1,1). I construct this model on 1000 observations and find the forecast for following, for example, 100 observations. But it' s necessary for me to get the predicted values of the previous 100 observations and compare it with actual values. Please, tell me what should be done. Thank you very much [[alternative HTML version

Hi, I am trying to forecast a model using predict.Arima I found arima model for a data set: x={x1,x2,x3,...,x(t)} arima_model = arima(x,order=c(1,0,1)) I am forecasting the next N lags using predict: arima_pred = predict(arima_model,n.ahead = N, se.fit=T) If I have one more point in my series, let's say x(t+1). I do not want to recalibrate themodel, I just want to forecast the next N-1

Hello everybody! I'm having this problem with the auto.arima function that i've not been able to solve. I use this function on time series that contains NA values, but every time that the resulting model contains drift I can't perform a forecasting (using forecast.Arima function). The printed error (when I try to forecast the resulting model) claims a dimension mismatch

Dear friend, hope you are doing great, I have the following code: > myTseriesData <- ts(data[,2], start=c(2000,01), end=c(2017,9), frequency=12) > myTseriesModel <- auto.arima(myTseriesData, d=1, D=1) > myTseriesForecast <- forecast(myTseriesModel, h=12) > # I want to be able to format the dates generated by the forecast function is there a way to change the format of the