# Tagged Questions

Refers to the AutoRegressive Integrated Moving Average model used in time series modeling both for data description and for forecasting. This model generalizes the ARMA model by including a term for differencing, which is useful for removing trends and handling some types of non-stationarity.

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### How to Add Kalman Filter/Forecast to Seasonal ARIMA model in R

I need to compute a seasonal ARIMA model and make forecasts using Kalman filter. I do not understand how to feed the output of SARIMA((p,d,q)(P,D,Q)s) to kalman filter. Apart that there are many R ...
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### Choosing regressors for inclusion in regression with ARMA errors

I would like to conduct a forecast based on a time series ARIMA-model with multiple exogenous variables. My time series is monthly unemployment data (in percentage) during several years and my ...
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### In ARIMA with differencing (I>0), how are prediction intervals for forecasts calculated for the original (undifferenced) series?

In ARIMA with differencing (I>0), when producing forecasts, how can I go from prediction intervals for the differences to prediction intervals for the undifferenced series? My guess is, since the ...
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### Deciding the value of period in seasonal ARIMA (R)

I'm new to time series modeling and am trying to do seasonal ARIMA modeling here. I have figured out the p,d,q values but im not sure how to select the period in the below formula. There seem to be ...
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### How to handle multiple seasonality in ARIMAX model?

x and y are two multiple seasonal time series and I want to check if the argument x has got influence on y. Both time series have the same multiple periodicity. I've read in some comments on the blog ...
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### Forecasting seasonal components in X-13ARIMA-SEATS

Forecasting seasonal components is an important practical problem in finance, where products that are highly exposed to monthly seasonality in consumer prices are traded. For example, one can trade ...
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### What is the difference between VAR, Dynamic Regressive, and ARMAX models?

All of these models seem to be used in predicting an endogenous time series variable, using several lagged exogenous time series variables. If it is so, how do we decide when to use which?
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### ARMAX or Dynamic Regression | regression of multiple timeseries

I have the following time series dataset (dependent | independent) : Sales | Income,Inflation, Interest Rates etc All of this is dynamic data pertaining to each ...
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### Extracting X-13ARIMA forecasts of seasonal effects [on hold]

I am attempting to forecast seasonal effects in various consumer price index components (foods, services, goods, etc.). In other words, I am interested in obtaining - for each time series - forecasts ...
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### Detailed reference to facilitate manual implementation of ARIMAX

ARIMAX is implemented in SAS and R (function arimax in "TSA" package). I want to implement ARIMAX in an open source library in Scala and Python. Is there any ...
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### Why does the Arima() method in the forecast package in R not calculate standard errors for coefficients passed to 'fixed'?

In the Arima() method, in the forecast package in R, I can provide a vector of parameters to the ...
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### Time series prediction using ARIMA

I have a dataset which contains data from a sensor for every 5 minutes and am trying to predict for example 10 future values based on the first 500 values. My data looks like the following and could ...
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### Using an ARIMA model to create an adjusted (normalised) time series

I am examining monthly road accident counts over the last 25 years. I have created an ARIMA model in R using rainfall and temperature deviations from the long-term monthly average as exogenous ...
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### Estimation and forecasting ARMA: differences between Matlab and Stata

I have to forecast values from an AR(1) model. My sample is composed of 192 observations. I estimate my model with the 182 first observations and forecast the 10 last observations. I have done this ...
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### ARIMA-GARCH instead of ARIMA for intervention analysis

I'm looking to carry out an intervention time series analysis on the S&P500 to see how presidential elections affected the stock market. I want to use an ARMA-GARCH process to model S&P500 ...
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### SARIMA model on original (unstable variability) or transformed (stabilized) series?

If my series requires a log-transformation to stabilize variability, do I apply the sarima function to the log-transformed series or the original series? Does the ...
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### Forecasting ARIMA with predict vs forecast in R [closed]

Data consisting of 30 values is stored in a time series time. After applying ARIMA modelling on time, I used ...
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### What is the difference between ARMA+Fourier and TBATS model?

I am just wondering that, in terms of the multi-seasonal time series forecast, what is the difference between using auto.arima find the ARMA order, then fit <...
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### Order of ARMA models

Why we usually do not exceed ARMA(5,5) models in practice? Is there any mathematical justification for this?
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### How to convert hourly data into a time seris in R [migrated]

I have hourly data arranged by date and the dput is given below: ...
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### AIC only applicable to maximum likelihood fit (not least squares)?

When I read about AIC I see that it is calculated for maximum likelihood model estimation. For example, R function arima0 estimated by ...
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### What do coefficients of auto.arima mean?

After running my auto.arima model I'm getting coefficients ar1, ar2 & sar1. What do these coefficients mean?
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### X13 Arima with negative values

I'm running x13 Arima analysis on a US GDP series to get the "trend" component. ...
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### Time series with 24 yearly data points - advice needed

I have a dataset containing the prevalence rate of Malaria in Botswana, starting in 1990 and ending in 2014. My task is to verify whether these data can be used in order to make predictions on the ...
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### forecast using an ARIMA Model

I'm using the R function auto.arima to fit an arima model for a time series, the result is an ARIMA(2,1,1). After that I apply the ...
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### Parameter estimation for ARIMA around a complicated deterministic mean

Currently, I am trying to fit a time series to the following model: $$(1-\phi_1B-...-\phi_3B^3)(y_t-\mu_t)=\varepsilon_t(1-\theta_1B-...-\theta_3B^3),$$ where $t=1,\dotsc,n$ and $y_t-\mu_t$ is ...
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### Choosing between ets or arima model

I have a time series and two models to choose from: ETS and ARIMA. I have used the MAE to select a model. But when forecasting the time series and comparing the models, I don't know which model ...
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### Questions about how to choose the best arima model to forecast

I'm trying to forecast the prices of gold, silver and platinum for the next 10 years using an ARIMa approach. After treating for the basics I am now stuck on the decision of which model to fit best; ...
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### Different AIC values in trace and final output in auto.arima

I am trying to fit a time series with function auto.arima in the "forecast" package in R that is choosing the best model automatically. Since I am using it for my ...
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### Forecasts from ARIMA(1,1,0) ignore the mean value

I am estimating an ARIMA(1,1,0) + constant model. The program also reports back a mean value. However, the program's forecasts ignore this mean value. Why?
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### R-Monte Carlo simulations for ARMA model [closed]

I have 5 years of daily price data of an asset for which I have fitted an ARMA model. I want to generate 10000 simulations for next 6 months using the last available value for the asset as starting ...
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### Arima time series

I am trying to build a arima time series model for demand prediction... my data is on weekly level from 2014 and 2015 all weeks. If I also use 2016 first 10 weeks data and then try to predict the for ...
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### How to manually predict one step ahead time series data using coefficientes estimated by arima function in R

My objective it to manually compute one-step ahead forecast using the estimated coefficientes given by the arima function in R. I will consider the specific model ...
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### Coefficient bias in ARIMA vs. lagged regression

I am trying to estimate the effect of an external regressor $x_t$ on a time series $y_t$. My first attempt was using an ARIMAX(p,d,q) Model to estimate $\beta_x$ while controlling for the ARMA ...
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### Determine best ARIMA model with AICc and RMSE

I have done a training set to fit different ARIMA models and then a test set to assess their performance (with R). From what I understood, I can use the AICc to determine the best model by choosing ...
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### Changing sensitivity (cval) in tsoutliers resulting in unexpected results

I am using the excellent tsoutliers R package to detect outliers (additive outliers, temporary changes etc.), but the cval ...