1. M

    time series analysis

    There is an aggregated measure represented by a variable A, modeled as a time series from a process. There was a need forecast A and also to find out the historical amount of data of A that is the best reflector of future values of A (as there was a data storage capacity issue). Using a...
  2. M


    There is an aggregated measure represented by a variable A, modeled as a time series from a process. There was a need forecast A and also to find out the historical amount of data of A that is the best reflector of future values of A (as there was a data storage capacity issue). Using a...
  3. M

    Simulation of technical analysis indicators

    Hello! :wave: I have to test effectiveness of technical analysis indicators. Major problem is that I don't know how to correctly use output of arima.sim. I did sequantially: In order to conduct this study I created ARIMA model based on real data: data <-read.csv(file="enea.csv"...
  4. M

    Which is the better prediction model?

    The aim is to predict the breakdown time of a machine as a percentage of scheduled hours for the next day. So my time series looks like this, Break_down_percentage = 7%, 8%, 10%, 6%, 12 % etc. There are 315 data points which can be used to test the different models. I used ets(), arima()...
  5. M

    updating ARIMA model

    When should one use the different types of ARIMA model as mentioned below: Estimate the model order in the training data set and use the same order to forecast future values (updating the parameter estimates) Use a rolling window (e.g. 30 day )to make a new forecast by estimating model order...
  6. L

    Partial Autocorrelation Function

    Hello everyone, I am preparing for a test and I have came across a question I am having problems with: Calculate partial autocorrelation of first and second order in the fillowing model: y[t]=-0.7*y[t-1]+e[t]+e[t-1] any solution or hints on that?
  7. Y

    how to fit the auto arima model

    hi guys, Im new to R and I got a problem unsolved for several days: I got a dataset which covers three years by week and I ran an auto arima on the train data set which is 80% of the original data set. Then I got the following result: ARIMA(1,0,0)(0,1,0)[53] with drift Im wondering how...
  8. A

    R Arima Equation Question - Please help!

    Hello, I am new to R and I am trying to conduct a time series ARIMA analysis for my work.
  9. J

    MA() part of ARIMA: How do you get error terms?

    I've been through the excellent forecasting book coauthored by Hyndman on I'm having trouble understanding the actual algorithm. The MA(x) is supposed to be a moving average of error terms. But where does the error come from? Is it based on the AR(x) term? In that case, what about...
  10. E

    Time Series with Multiple Intervention Dates

    I'm working with a time series in which the same intervention was applied to a large number of items but at different points. Essentially, I have figures by day (and can roll them up by week, month, etc.) and I am trying to figure out what the impact of the intervention is on the figures. The...
  11. T

    Selection of forecasting method - Winter/ARIMA/TBATS in R

    Please find my dataset and forecast outputs attached. A) First sheet contains March-2011 to February 2014 data and forecast for March-2014 to February 2015 using ARIMA,Winter's,TBATS and BATS method.It also has forecast errors obtained by comparing with actual output. B) Second sheet has...
  12. U

    How to run a lagged (time series?) model in R?

    Hi there, I am wanting to run a lagged model where a predictor (X) at T1 is regressed on an outcome (Y) at T2, controlling for Y at T1 plus 2 covariates at T1, over a total of 20 time points (so as to test whether X causes Y). I could use a cross-lagged SEM in Lavaan, but most papers I've...
  13. N

    rollapply with Arima model: testing for stability of coefficients

    Hi everyone, I am trying to fit an arima model on a rolling window using rollapply.My aim is to plot a graph of the evolution of the coefficient, plot the error and the standard deviation. well i encountered the following problems: 1) each window in the roll apply have different set of...
  14. S

    Acf Pacf interpretation for ARMA modeling

    Hi, I have trouble interpreting acf and pacf of the stationary series depicted. Could I receive some suggested interpretations, with focus on determining ARMA(p, q) order? Thanks, please let me know if i should give more information. Edit: I added a spectrum plot. Because if I'm...
  15. I

    Is ARIMA model appropriate for this dental research?

    Hi members. Please, I have a doubt in my study for doctoral thesis… Title: “Development of a thermal cycling protocol for dental materials”. Objective: to create a protocol for thermal aging, from measurements that were found in people mouth. Doubt: What analyses could I use for this...
  16. M

    Tim series Analysis in EViews

    Hello Everyone,I have a question which may be very simple .For Example I have estimated ARIMA(1,1,4) from a data having sample 1961-1999.To produce forecast I re-estimate sample from 1961-1995 and then its easy to produce forecast on eviews.I want to confirm forecast produced by EViews manually...
  17. F

    Automatically make out-of-sample forecasts on SPSS

    Hi everyone! I'm a little stuck on a problem on SPSS and I really hope you might help me. For my master thesis I am trying to elaborate a statistical model for forecasting Consumer Confidence time series. The model I'm using now seems to work great in in-sample forecasts, but how can I know...
  18. S

    R code error for ETS

    Hi I use the following R codes for ETS forecasting in my Rexcel, but whenever the frequency of the data is high there is an error and the code do not run. Given below are my codes: #!rput library(forecast) zz <- ts(zz,freq=365,start=c(2009,1)) etsz <- ets(zz,model="ZZZ") etszP <-...
  19. F

    How to calculate ARIMA(1,0,1)

    Hello, I want to forecast the 101th data of a time series and my data is as follow 99) 0.96 100) -0.2495 101) ? and my model Coefficients: ar1 ma1 intercept 0.6769 -0.4255 0.0019 s.e. 0.1210 0.1505 0.0876 By using R I know answer is 0.084036 but I...
  20. F

    Assumptions for an ARIMA(p, d, q) model (Box-Jenkins)

    I have a data set which is stationary but the histogram looks like a logaritmic distribution. Is this a problem? Is normality an assumption to use this model? what should I do? Thanks