Questions tagged [arima]

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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19 views

Statistical significance of an event in seasonal time series

Goal I am analyzing multiple time series data. I want to show there is difference in trend of the data after an event happens, either right after or a bit later, and it is statistically significant. ...
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auto.arima vs arima.sim

I noticed auto.arima is frequently giving a different model than simulated with arima.sim, so I tested it crudely: ...
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Multiple Time Series in one Auto_arima code

I hope you can help me with the following. I am using the Auto_ARIMA function (pmdarima library) to calculate my p, d and q ...
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How if the coefficient constant Insignificant when Estimate ARMA?

I'm doing my thesis about estimate Volatility where I use ARMA for Mean Equation. when I'm trying to estimate the ARMA, I get Insignificant for coefficient constant but the AR and MA both are ...
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At what point during ARIMA series model building should log transformation be considered for variance stabilization?

Data: http://fred.stlouisfed.org/series/ECOMPCTNSA Model Build: Seasonal ARIMA Model Program: R I am building a Seasonal ARIMA Model to model the quarterly time series data which can be downloaded ...
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How to forecast an ARMA model with a white noise error term and an ARMA model with an ARCH/GARCH/TGARCH

I need to estimate An optimal ARMA (p, q) with a stationary error term (assuming a white noise error term). And an optimal ARMA (p, q) with autoregressive conditional heteroskedastic error structure (...
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Improving ARIMA forecasts

I am trying to use ARIMA to forecast stock returns. The problem is that variance is time-varying but ARIMA assumes that it is constant. As I understand, GARCH is only used for forecasting volatility (...
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7 views

SARIMA (1,1,1)(0,1,1)12 interpretation

How do you interpretate the dependencies among your observations if your model has the form SARIMA (1,1,1)(0,1,1)12. What conclusion can you draw on the long term dependencies as well as the ...
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Why the fitted values are generated from the first data when running arima() in R?

When we run arima() in R, for example, y<-ts(InflationRate[,'Inflation'],start=c(2011,01),frequency=12) model<-arima(y, order=c(12,0,0)) residuals(model) And my results look like: This is an ...
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How do you find the coefficient values for the unique causal solution of $\text{AR}(p)$?

I am working with a causal $\text{AR}(p)$ model. I know I can express this in causal form as: $$X_t = \psi(B) W_t \quad \quad \quad \psi(z) = \theta(z)/\phi(z).$$ I also know that the parameters ...
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Time Series Forecasting with (week)day data in R

I was hoping to ask this community for a little advice. I’m doing a bit of daily forecasting, and, because it has always served me so well, I’m using Prof. Hyndman's now famous 'forecast' package. At ...
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Chosing seasonality frequency

i am trying to build a general forecast at work, but i am in trouble about the frequency of my series. Can a subject reason guide me through the frequency selection? I have daily data, so i could ...
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Help selecting ARIMA model whilst using ACF and PACF graphs

I have 20 years of quarterly data regarding investments. I am attempting to forecast future investment levels using SPSS. I have used seasonal decomposition to remove seasonal effects from the data, ...
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How to conduct series of ADF tests on data in correct way?

I was trying to fit an ARMA model for some data. It was easy to spot that data is non-stationary, so I decided to conduct ADF test on it and it turns out that I was right. Then I took the first ...
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Can I include forecasted values as explanatory variables when forecasting?

I am wondering about a problem I have encountered. If I were to use income as an explanatory variable in an ARIMA model to forecast consumption, I would need future values for income to include in ...
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Forecast ARIMA and out of sample evaluation

I have a train daily data and test daily data. I fit an ARIMA to my train data, forecast it 7 days and I want to get some performance measures of the forecasted values. I can get performance measures ...
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Comparing Neural Network to ARMA

I used a neural network tool in MATLAB to predict data, and it gave it's accuracy as MSE and an R-value. I used the econometricModeler tool in MATLAB to predict data using ARMA. It gave it's accuracy ...
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How to choose between these 2 Arima models

I have two Arima models with interventions. Both used automatic procedures to find the interventions. The forecasts diverge a lot, mostly because of the drift term in model 1. How can I ...
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Different ARIMA models for forecasting sales of many products, or one ARIMA model for all of them

I have sales data for many products, my task is to do an ARIMA model to forecast sales for each product. I've done a tailored ARIMA model for each product as they exhibit different patterns. Then ...
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Using ARIMA to explain time series data

I am creating models to analyze energy use in four U.S. states. The goal is to create a model to explain historical data (1960-2009) as well as to create a forecast for 2025 and 2050. I am using R and ...
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Expressibility of VAR(1) models

Am I correct in understanding that vector autoregressive (VAR) models of order one can capture seemingly more general modeling frameworks such as VAR(p) models, for orders $p > 1$, and ARMA models? ...
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Write R code of AR(2) model for a time serie data from `rsav` file [migrated]

I need to write R code to model a time serie data from rsav file. Here is detailed information about the question: The file ...
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Determining order of SARIMA model by ACF/PACF (and dealing with seasonality)

I have a ts that has the average monthly measure of pollutants in the air and i'm trying to use a SARIMA$(p,d,q)(P,D,Q)$ to model it but I'm having trouble determining the order because I'm somehow ...
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Distribution of forecast error of ARMA + GARCH model

I am modelling a time series process and want to explore ARMA + GARCH. Using ARMA alone, with normally distributed residuals, we can determine the distribution of the forecast error using the ...
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Compact notation of ARMAX model

I was trying to create a compact equation for an ARMAX model with ARMA(1,1) and 3 lagged predictors? The expanded equation looks like this: $$y_t = -103.784 + 0.075 x_t + 0.058 x_{t-1} + 0.008 x_{t-2}...
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What is the fitted TFN model for this ARIMA (1,0,1)?

This is the ARIMA model: Regression with ARIMA(1,0,1) errors Coefficients: ...
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auto arima with stepAIC and PCA

Can auto arima be used in conjunction with stepAIC or principal components analysis? I have several regressors and I don't know which ones to use in auto arima. I was hoping to use stepAIC to help me ...
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R Forecast Package: Why are my in-sample simulations consistently higher than the original time-series when using the simulate function?

What I want to do: Fit an arima model with an xreg component using auto.arima and then generate simulations in-sample where I pass in different xreg values. The issue: After fitting an arima model (...
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Choosing ARIMA lag orders based on ACF and PACF: a case

Trying to figure out arima parameters. Performed dicky fuller test to make sure no unit root exists at the first difference. When plotting the pacf and acf, how do I chose AR and MA parameters for the ...
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Suitable model to be trained on Chinese COVID-19 data in order to forecast other countries data

In an article by WHO (World Health Organization) published on February 24, they present a very interesting plot (page 7) comparing symptom onset vs diagnosed cases for China. Since there is a lag time ...
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Time Series Preprocessing

I am just here for brainstorming as time series prediction can be storming to the brain. so basically working with time series prediction doesn't usually follow the same rules as working with other ...
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Forecasting 75 steps into the future ARIMA(1,1,1) Model EViews [closed]

Good afternoon, I have an economics time series of around 3300 daily observations that go over 10 years. I already developed and ARIMA(1,1,1) Model based on the autocorrelation and partial ...
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SARIMA nonstationary: how to remove trend and seasonality?

I have a database with hourly records. When I perform my ADF and KPSS test the p-value is less than alpha 0.05 so the series is assumed to be stationary. But by plotting the ACF the delays are all out ...
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When to use ARIMA model vs linear regression

I am trying to forecast time series of product sales, I started approaching the problem by implementing the ARIMA model, I iterated over all the possibilities of the models parameters (p, d, q) and ...
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What is the exact defenition of ARMA model in statsmodels and how to predict the next value using the summary of the fitted model manually?

I've fitted a time series (Y) on the ARMA(2,1) model using statsmodels in python. let's leave alone that the selected order is ...
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What is the best way to model such time series?

I have this time series where a peak occurs every around 5 years and the structure changes after each peak. What do you think is the best way to model such time series? Can this be modeled using the ...
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Arimax not giving standard error for transfer function model

I'm trying to fit an ARIMA(0, 1, 1)(0, 1, 0)[4] model to some quarterly data, with an additive outlier(AO) at time point 11, and a transient change(TC) intervention at point 31. I am having an issue ...
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Is it necessary to include the identified AR or MA parameters in a dynamic regression model?

I am performing a univariate and multivariate time-series analysis. After identifying the best ARIMA models for each individual time-series, I performed the cross-correlation function to identify the ...
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Determining order of ARIMA(p,d,q) from ACF and PACF

I know that when trying to determine if you have an AR(p) or MA(q) process, you look at the PACF and if it drops off significantly at a lag p, then you can say it's an AR(p), but if it's geometrically ...
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What is the take away from such ACF and PACF plot?

I plotted the ACF and PACF after taking the first difference of my time-series. What is the take away from such plots? What should be the AR and MA order in such case? The data is as follows, <...
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A solution to de-seasonalizing data? Admission rate to emergency room

I am trying to fit a model for the admission rate to our emergency department by using time series in STATA, which is fairly new to me and I would like to take your input about deseasonalizing. data:...
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Time series analysis and cross-validation with slide-window

I m trying to understand the time series analysis and cross-validation with slide-window. My question is inspired to this other question on 冠通棋牌-【官网首页】 but it wants go deep in this argument with ...
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1answer
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Should I deseasonalize my time series before using SARIMA?

I have the following time-series that I need to model using SARIMA. There is a clear seasonality pattern but there is no apparent trend. Should I de-seasonalize (seasonal differencing) my time series ...
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NEED A LITTLE HELP WITH “D” PARAMETER IN ARIMA

My question is very simple: If my time series aren't stationary, and I diff it one time before fit the model, i need to put 1 on my ARIMA "d" parameters or i only need to do this if i don't diff my ...
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What could indicate autocorrelation from the below correlogram?

I would like to ask you a question about autocorrelation from my table. Autocorrelation slows down and then it is up and again slows down. It could indicate non-stationarity of time series?
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What kind of ARIMA Model is this?

I've got the time series $Y_t = 3 + Y_{t-1} + e_t - 0.75e_{t-1}$ and I'm trying to figure out what p,d,q are for the ARIMA(p,d,q) model. looking at the $e_t - 0.75e_{t-1}$ part I'd like to say there'...
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ARMA model coefficient Interpretation

How do I interpret the phi and theta in the SARIMA model? I know that they are both parameters of the model, but I am having a hard time trying to interpret them. For example, the phi in the AR(1) ...
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Parametrization hourly data in cycle for in forecasting problem

I try to explain my programming problem. Dataset: 26 variables, 1176 hourly values Goal: Find optimal method to forecast next 24 values. I separated my historical data in training and test dataset in ...
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Using ARIMA model FOR EL NIÑO FORECAST, Need some TIPS

I'm using ARIMA (setting up ARIMA to go to ARIMAX) from statsmodels to build a model to predict el ninõ, currently i have 5066 daily data from Niño 34 AREA SST Anomaly, we generate this on lab with te ...
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Forecasting a multivariate time series with few observations

I am trying to forecast the number of confirmed cases for several days (1, 3, a week) of a virus with the following data: ...

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