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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1answer
21 views

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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9 views

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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1answer
14 views

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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31 views

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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8 views

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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2answers
46 views

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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29 views

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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6 views

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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43 views

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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1answer
25 views

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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1answer
45 views

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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1answer
29 views

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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18 views

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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1answer
29 views

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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1answer
19 views

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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1answer
30 views

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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0answers
30 views

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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1answer
26 views

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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10 views

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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1answer
58 views

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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2answers
52 views

Predict from estimated ARIMA model with new data

Suppose I have a training dataset, I use auto.arima (from "forecast" package in R) to fit the training data. As a result I get the lag and integration orders $(p, d,...
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23 views

How to extend the separated trend line to predict future time series values in R?

We have data from border router devices that depict the bits per second from the past 4 years. There are some missing values or values too low when backup devices were in use. Every day has a BPS ...
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2answers
56 views

Arima and lm not giving same coefficients in R

I'm fitting an arima(1,0,0) model using the forecast package in R on the usconsumption ...
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11 views

What is the SARIMA (2,1,0)(0,0,1)_12 euqation? [duplicate]

I have problems to find the euqation for Arima (2,1,0)(0,0,1)12....would be nice to get some help!
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2answers
52 views

Modelling moving holiday effects in forecasting

I have researched multiple related questions(here, here) but it lacks detailed context and solutions. My goal is to improve my daily sales forecast accuracy after having incorporated a simple holiday ...
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30 views

Interpretation of the ARIMA coefficients in a time series

I am trying to understand the coefficients retrieved when placed the command auto.arima to my monthly time series of the annual change in House prices. When doing ...
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1answer
60 views

Time series prediction using ARIMA vs LSTM

The problem that I am dealing with is predicting time series values. I am looking at one time series at a time and based on for example 15% of the input data, I would like to predict its future values....
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1answer
40 views

Applying different time series models (ARIMA, HOLT-WINTER) on the basis of MAPE

I have a time series object calc_visit_ts. I want to apply the best fit time series model based on the MAPE value for each model. The issue I face is that the MAPE ...
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1answer
24 views

Are spectral decompositions of time-series useful for modeling/forecasting, or are they more of a tool for analysis?

This is a bit of a theoretical question. I'm also new to time-series analysis, and trying to learn fast. Sorry if some of my terminology is off. You can loosely categorize methods to analyze and ...
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31 views

Test difference between two short time series

I have data on leukocyte aggregation (a percentage) in two different conditions (A= control, B= Verum). Blood was sampled 8 times throughout the day in 2h intervals. I'm fairly new to statistics and ...
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1answer
41 views

Using a function of intervention time as a covariate in arimax

I am trying to estimate the impact of an intervention on a time series. The problem is that the intervention effect looks curve-linear (i.e. increasing, plateauing, and then decreasing), and I am ...
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1answer
38 views

Is this an SARIMA(0,0,0)x(0,1,4)_12?

I found someone's quick-and-dirty forecast of a variable $x$: $$\hat{x}_t = x_{t-12} + \frac{1}{4}\Delta_{12}\left(x_{t-1} + x_{t-2} + x_{t-3} + x_{t-4} \right)$$ Can this be viewed as an "optimal" ...
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33 views

Analyzing residuals vs fitted values in a time series

I fitted a times series using an ARIMA(6,1,0), and tried to analyze the residuals, I wrote a code that gave me same four plots as in the lm R function, the one I'm interested in the last one where I ...
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1answer
61 views

How to deal with hourly non-stationary time series data with multi-seasonality?

I currently have hourly electricity demand data last for 5 years, where I used: demand <- msts(mydata$DEMAND,seasonal.period=c(24,182.5*24,365*24),start=2012) ...
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1answer
26 views

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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1answer
21 views

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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2answers
58 views

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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26 views

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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29 views

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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20 views

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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27 views

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; ...
3
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1answer
25 views

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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0answers
12 views

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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59 views

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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21 views

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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0answers
28 views

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 ...
0
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1answer
26 views

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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30 views

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 ...
2
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0answers
28 views

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 ...