Statistical Analysis Stack Exchange
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Questions tagged [box-jenkins]

The Box-Jenkins procedure is used to identify the orders of an ARIMA model to apply to a time series.

The Box-Jenkins procedure as proposed by Box, Jenkins & Reinsel (Time Series Analysis - Forecasting and Control, 3rd ed., 1994, section 6.2) proceeds by first identifying the degree of differencing necessary to achieve a stationary time series, then identifying the orders of an ARMA process that yields white noise residuals when applied to the differenced series. It relies mostly on visual inspection of (partial) autocorrelation plots.

Variations involve using information criteria like the AIC or BIC instead of the (P)ACF. Many forecasting software packages have automated the Box-Jenkins procedure so it can be automatically applied without an expert to assess (P)ACFs.

More information can be found in this CV thread: What exactly is the Box-Jenkins method for ARIMA processes?

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Moving-average model error terms

This is a basic question on Box-Jenkins MA models. As I understand, an MA model is basically a linear regression of time-series values $Y$ against previous error terms $e_t,..., e_{t-n}$. That is, the observation $Y$ is first regressed against its…
Robert Kubrick
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ARIMA estimation by hand

I'm trying to understand how the parameters are estimated in ARIMA modeling/Box Jenkins (BJ). Unfortunately none of the books that I have encountered describes the estimation procedure such as Log-Likelihood estimation procedure in detail. …
forecaster
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Box-Jenkins model selection

The Box-Jenkins model selection procedure in time series analysis begins by looking at the autocorrelation and partial autocorrelation functions of the series. These plots can suggest the appropriate $p$ and $q$ in an ARMA$(p,q)$ model. The…
Charlie
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Determining parameters (p, d, q) for ARIMA modeling

I am fairly new to statistics and R. I would like to know the process to determine the ARIMA parameters for my dataset. Can you help me figure out the same using R and theoretically (if possible)? The data range from Jan-12 to Mar-14 and portrays…
Raunak87
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Relation and difference between time series and regression?

What are relation and difference between time series and regression? For models and assumptions, is it correct that the regression models assume independence between the output variables for different values of the input variable, while the time…
Tim
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Autocorrelation in the presence of non-stationarity?

Does the autocorrelation function have any meaning with a non-stationary time series? The time series is generally assumed to be stationary before autocorrelation is used for Box and Jenkins modeling purposes.
griffin
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What exactly is the Box-Jenkins method for ARIMA processes?

The Wikipedia page says that Box-Jenkins is a method of fitting an ARIMA model to a time series. Now, if I want to fit an ARIMA model to a time series, I will open up SAS, call proc ARIMA, supply the parameters $p,d,q$ and SAS will give me AR and MA…
Victor
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What are the assumptions of ARIMA/Box-Jenkins modeling for forecasting time series?

What are the assumptions of ARIMA/Box-Jenkins modeling for forecasting time series?
forecaster
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Review of Box-Jenkins methodology

i just finished developing an ARMAX model with python (mostly statsmodels) in order to forecast some data. My next step is to test the data (24 time series) with the given ARMAX model. As i need to write a proper academic documentation about all…
Peter Knutsen
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Poisson regression with (auto-correlated) time series

I have a time series dataset which shows, for each day, the number of complaints received by an organization about a particular problem. I also have a number of other time series for the same period (mostly environmental variables like weather,…
JamesS
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How can I check if my time series data is zero mean, stationary and independent identically distributed?

I have time series data which is international monthly tourist arrival to Malaysia (N=264). My objective is to forecast tourist arrival for 6 months ahead. After analyzing my data pattern, I found that using Box-Jenkins method gives me the best…
Ariffin
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Selecting ARIMA orders based on ACF-PACF vs. auto.arima

I use R to fit an ARIMA model to a time series (yearly granularity): library(forecast) beer <- c(150,241,361,403,504,684,706,862,879,806,840,846,1024,1196,1239,1237,1281,1342) ts_beer = ts(beer, start = c(1980), frequency = 1) dif.ts_beer <-…
Mark K
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Predicting forecasts for next 12 months using Box-Jenkins

I am building a Box-Jenkins model in Excel using solver. The model is AR(2). The data that I have contains trend and seasonality both. I know how to remove seasonality using seasonal indexes and add it back to the forecast. But, how do I handle…
Abhishek
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What is the ARIMA model for this data?

I have made my series stationary by using one difference and have plotted the following acf & pacf: So I have decided to test the following models: • ARIMA(0,1,1) since the acf cuts off after lag one. • ARIMA(1,1,0) since the pacf cuts off at…
CCZ23
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Fitting a Multivariate ARIMA Model (in R)

I've been working on a high school project attempting to determine whether or not there exists a relationship (and if it exists, information on the strength and duration of the relationship) between stock market data and election polls (both in time…
Johnathan Stimpson
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