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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9 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
17 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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11 views

Predicting with function `arima` producing NaN values in R [on hold]

I am using arima function for intraday forecasting. Data is available for every 15 minute in a day. In the code below, it is working fine except for a few values of ...
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1answer
20 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
17 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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1answer
44 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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12 views

Autoregressive and moving-average models [on hold]

I have been trying to fit AR and MA models separately using ACF and PACF but unable to progress using STATA. I have run the ACF and PACF plots at 95%. ACF is cutting off at lag 11 and PACF at lag 8. ...
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0answers
19 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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26 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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0answers
16 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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0answers
20 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
19 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
9 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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0answers
46 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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0answers
20 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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25 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 ...
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1answer
22 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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0answers
25 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 ...
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0answers
19 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 ...
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0answers
33 views

When to use Exponential Smoothing vs ARIMA?

I have recently been refreshing my forecasting knowledge while working on some monthly forecasts at work and reading Rob Hyndman's book but the one place I am struggling is when to use an exponential ...
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21 views

How do I recover parameters from ARIMA?

Given a simulated time series test.ar <- arima.sim(list(ar = c(0.8, -0.2)), n = 1000) I hoped to estimate the coefficients (0.8 & -0.2) using ...
3
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0answers
20 views

Stationarity of independent variables in ARIMAX

I am running an ARIMA model with exogenous variables. Do all my exogenous variables have to be stationary or is it okay if one of my exogenous variable is non-stationary?
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19 views

Test for nonlinearity of regression model with ARIMA errors in R?

I would like to do regression with ARIMA errors in R with TropBirds.ts as response variable and ForFrag.ts as explanatory ...
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20 views

How can I decompose the error after an ARIMA estimation, and how do I store the estimated values?

EDIT (in response to Stephan's comments): I was able to read a paper by Bessembinder & Seguin (1992) on futures trading and stock price volatility, wherein they used the ARIMA model to decompose ...
2
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1answer
91 views

How to optimise an automatic ARIMA-model selection?

I've been using statsmodels.tsa.arima_model to fit the residual component of some data. I've written an algorithm to automatically select the ARIMA model. Results ...
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1answer
25 views

Pacf lag axe , is not an integer

I'm trying to use ARIMA process to predict the behaviour of a time series, the probleme I face is that I can't get the order of each component of ARIMA, the lag is between 0 and 1, same goes for the ...
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0answers
26 views

Is there a way to prevent forecasting negative values with ARIMA (or add constrains) in R?

Currently I'm using the ARIMA provided in R, the training series is a seasonal time series, with some values close to zero in each period, and I find that when the training series have a descending ...
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0answers
22 views

Removing seasonality when timeseries includes negative or zero values

I am using an x13-arima-seats based solution to remove seasonality and detect data trends. However, many of the series I need to observe trends on contain zero and negative values, which my solution ...
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0answers
14 views

How to compare multiple time series with a single time series and quantify upward/downward trend relative to the single time series?

I have been reading about time series comparison and haven't really found an answer to my question. I have around 1000 stores which I have clustered based on trend over time and identified 8 groups of ...
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1answer
43 views

Which are the basic steps of the stock price forecasting using ARIMA model in R?

I am very new to this field and I want to learn forecasting of stock price using R. Please let me know which are the step should I follow? If someone know tutorial links for forecasting in R then it ...
1
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1answer
42 views

Fourier terms to model seasonality in ARIMA models

I would like to use Fourier terms to model seasonality in an ARIMA model. The reason for using Fourier terms instead of a seasonal ARIMA model is that the frequency of the time series is very high (...
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0answers
24 views

Seasonal ARIMA for each weekday instead of double seasonal ARIMA

I have read some papers on forecasting time series with double seasonality (e. g. hourly data with daily and weekly seasonality). I understand that double seasonal ARIMA can be used for that purpose. ...
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28 views

Matlab warning “linear inequality constraints active” when fitting ARMA(p,q) - GARCH(1,1)

With Matlab, I specified 9 ARMA(p,q)-GARCH(1,1) models and fitted all of them to monthly return data (I used GARCH(1,1) for every model but changed the ARMA order). Here is a very small example ...
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1answer
20 views

Hourly electricity demand data finding AR and MA terms [duplicate]

I am new to time series analysis. I have hourly electricity demand data for five years (having multiple seasonalities at intra-daily, intra-weekly, and annual periodicities) and I want to guess the ...
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0answers
19 views

How to estimate the variance of Box-Cox transformed data?

I refer to this question How to get the true mean forecast using the Arima package with a Box-Cox transformation Could anyone please tell me why is the variance of the Box-Cox transformed data given ...
3
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0answers
44 views

Decomposition of SARIMA models

I use R for time series analysis. I would like to evaluate decomposition algorithms. decompose and stl from "stats" package lead ...
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2answers
21 views

Scaling predictors in ARIMA model

If a predictor in an ARIMA model has much lower magnitude than the variable you are trying to predict, then do you need to multiply it by a scalar in order for it to be an effective predictor in the <...
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0answers
14 views

Negatively Correlated Predictors in Arima Model

If a predictor is negatively correlated with a variable you are trying to forecast in an Arima model, will Arima pick up the negative correlation when you add the predictor in the xreg argument? Is ...
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0answers
7 views

Combining Lower Correlation Predictors to Create Higher Correlation Predictors

I'm working on an Arima model to forecast a given variable and so I'm looking in my data for variables with correlation to the variable I'm trying to predict, to add as predictors in the xreg argument....
2
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1answer
29 views

ARIMA with high frequency data of only one month

I'm analyzing some data I collected for 4 weeks I would like to correlate a dependent variable ($y$) to other 10 independent metereological variables ($x_1, \dots, x_{10}$). ARIMA was suggested as ...
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0answers
8 views

Time-varying predictive model for a set of proportions

Suppose there is a casino where people bet on a weekly horse race. On Sunday, the casino publishes the prices for a wager on each horse for the upcoming Saturday's race. Everyone who wagers on the ...
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0answers
24 views

ETS or ARIMA model

I have a time series data set and want to predict my data in the future. I would like to when to use a ETS or an ARIMA model? Is is true that you can only use a ETS model when a data is non-...
0
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1answer
16 views

Residuals of SARIMA follow Student's $t$ distribution - implications?

I have fitted a SARIMA model to my time series. The diagnostics of the residuals are all good (ACF, PACF, ...), i.e. it seems they behave like white noise. But when I plot the normal qq-plot, they ...
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0answers
25 views

Obtaining $T$ residuals from AR($p$) model

I have my estimates for an AR(3). To obtain the residuals I'm supposed to use $$Y_t-\hat\phi_0-\hat\phi_1Y_{t-1}-\hat\phi_2Y_{t-2}-\hat\phi_3Y_{t-3},$$ where the $Y$'s are from the dataset. If I ...
0
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1answer
37 views

Testing intervention for a random walk using ARIMAX model

I am trying to analyze whether the intervention has an causal effect on $Y_{t}$. By ACF and PACF, it looks like the data is a random walk. I further use an ARIMAX model to examine the effect of the ...
2
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3answers
148 views

Seasonality not taken account of in `auto.arima()`

I am having basically the same issue than in this thread, except one thing: The difference, in my case, is that my data is measured weekly and not daily, so the argument of a too high seasonality (> ...
1
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2answers
100 views

Forecasting with multiple predictors and with multiple seasonalities in R

I have half-hourly electricity data of several homes for a duration of one month. Also, I have ambient temperature at same sampling rate. Now, I need to make half-hourly forecasts using historical ...
1
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1answer
27 views

How is mean calculated in ARIMA models?

I am currently working with ARIMA models and I am a little confused about the way they are formulated. I found Rob J. Hyndman's blog post "Constants and ARIMA models in R" explaining it. But still, I'...
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0answers
23 views

ARIMA model over- or underfitting: compare training and validation performance

I'm doing research using seasonal and nonseasonal ARIMA models. Here's the result of model identification: Based on many sources, Your model is overfitting your training data when you see that ...
0
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1answer
39 views

Mention day-wise seasonality for forecasting in ARIMA using R

I have half-hourly electricity data of several homes for a duration of one month. This data is represented in xts time-series format. Now, I need to make half-...