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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31 views

When to choose which model for time series?

What are the applications of AR and MA model? To put my question exactly, when to use AR model and when to use MA model(for example, like when it is seasonal or when there is a trend, etc). In other ...
2
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2answers
83 views

ARIMA model fits what kind of data

What kind of data fits ARIMA model well? If not ARIMA, what are the other good models that can be used to forecast the time series data?
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16 views

Finding the distribution of a pormanteau test

I am trying to find the distribution of a pormanteau test for lack of fit estimating an ARIMA(1,0,1) with white noises and fitting an ARIMA(1,0,1). I know this is not the best way to obtain a certain ...
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0answers
25 views

Large differences in ARFIMA parameter $d$ using different estimators

I am trying to estimate parameter $d$ for ARFIMA model using different methods: Hurst, ML, fdSperio, fdGPH and the function arfima which selects the best fit ...
2
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0answers
27 views

How to identify functional form of relationship between response & input series in dynamic regression/arimax?

Problem statement A US insurance company advertises on national television in an attempt to increase the number of insurance quotations provided (and consequently the number of new policies). ...
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0answers
11 views

Stationarity when using ARIMA/ARMA

Why do we need the dependent variable to be stationary when using ARMA/ARIMA? Aren't we already accounting for that autocorrelation by using ARMA terms? Isn't the whole point to use its ...
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0answers
14 views

Test MAPE < Train MAPE using auto.arima()

I am trying to build a forecasting model for the passenger vehicles registrations in a given country, and I wanted to use $auto.arima$ function from the $forecast$ package to estimate a simple ARIMA ...
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2answers
34 views

Traffic volume/flow prediction method

I have traffic volume data (Surrey City, CA) like this I wish to use Artificial neural network (Deep Learning) or ARIMA to predict traffic flow/volume of the urban area with the use of previous ...
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43 views

Bad results for R's auto.arima

I have a time series for sales data on a weekly and monthly basis. I tried using holt.winter and auto.arima. ...
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37 views

Using ARIMA to Create a Model in R

I'm trying to get understand why the values for my model are different when using two different functions. The first one is from Example 9.2 (International Visitors to Australia), using the ...
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0answers
17 views

Is ARIMA L-step forecasting the same as applying the model to values 1 to L?

My goal is to forecast sensor measurements (e.g. temperature, humidity) in a lightweight (and real-time) fashion. To this end I use ARIMA forecasting as implemented in R, where I retrain the model ...
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1answer
50 views

Breusch-Pagan Test for ARIMA Model in R

I am testing my model using the Breusch-Pagan Test, but have not been able to find anything online regarding how to calculate it for an ARIMA Model. My AR1 Model is: ...
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24 views

Fit ARIMA model to new data, preserving some coefficients in R

I create a demand forecast for a company that sells, say, toasters. We have one old standby model that's just finally stocked out, and a series of much newer models with shorter time series of sales ...
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51 views

Timeseries Regression - threshold value, regular and time-series covariates

i am trying to find a time-series regression or machine learning package that allows the following analysis: Lets assume that ice-cream sales are a function of: a) a threshold value on outside ...
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9 views

How to calculate manually the standard error that is calculated by arima model in MATLAB?

ARIMA(1,0,0) Model: Conditional Probability Distribution: t Parameter Value Standard Error t Statistic Constant 0.00548119 0.00116167 4.71836 AR{1} 0.050221 0.0879246 0.571183 DoF 5.44522 ...
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0answers
23 views

Regularization for ARIMA models

I am aware of LASSO, ridge and elastic-net type of regularization in linear regression models. Question: Can this (or a similar) kind of regularization be applied to ARIMA modelling (with a ...
2
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0answers
18 views

R: Dynamic Regression with ARIMA model using xreg, make use of step function?

This might fit better here than on stackoverflow, I guess. I was trying to build a dynamic regression model with the dynlm package, but it did not work out. After reading this by Hyndman, I now ...
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5answers
302 views

Is it always required to achieve stationarity before performing any time-series analysis?

For example, I know that for ARIMA models stationarity needs to be achieved. What about Exponential Smoothing? Is it also required?
3
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1answer
48 views

Explosive processes, non-stationarity and unit roots, how to distinguish?

I understand that if we have a simple model such as: $Y_t$=$\rho$$Y_{t-1}$+$\epsilon_t$ where $\rho$ is less than one in absolute value then we have a stationary process. If $\rho$ equals one then ...
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0answers
28 views

Backward ARIMA forecast

I want to try and predict previous values for random data that has properties of ARIMA process. Problem is that I dont understand ARIMA model mathematically, so I dont know if that's even possible ...
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1answer
73 views

Interpretation differences between deterministic seasonality and deseasonalized data with X-13 SEATS

I am running X-13 SEATS on r for monthly data in six years of observations and I think I got a (sufficiently) reasonable fit for the ARIMA model, but the output also shows me that my original series ...
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2answers
75 views

Is there a remedy for removing autocorrelations from residuals of seasonally fitted ARIMA model?

I fitted a number of SARIMA models using R and chose the ARIMA(0,0,0)(3,1,0)[12] as the best fitted model to the univariate data with 180 points (periodicity=12). This model is chosen as the best ...
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0answers
38 views

How to choose between VOMs and Predictive models, e.g., ARIMA?

In time series prediction, there is a lot of work that uses predictive models (e.g., ARIMA). On the other hand, there's also a lot of work that uses Variable Order Markov models (e.g., context ...
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33 views

Improving forecasting output obtained from Winter, ARIMA and TBATS method

I am trying to forecast commodity price for next year. I have collected and plotted monthly average prices from last 10 years.Plot has been attached. I used Holt's-Winter method on prices till 2014 ...
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3answers
117 views

Equivalence of regression models and ARIMA models?

I came across the below statement in this article: "An appropriate model for analyzing this time series in a least squares framework is to take the logarithm of the data and regress it on its lagged ...
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0answers
37 views

Box-Jenkins Forecasting With ARIMA(p,d,q) models

I want to check that I understand the general theme of forecasting with ARIMA models using box-jenkins, so I am going to take an example and then proceed from there. We will use $B$ notation for the ...
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2answers
90 views

Interpreting results of KPSS test in R

I've been trying to create an ARIMA model however, I'm not sure how to determine if the data is stationary or not. I preformed a KPSS test in R using kpss.test from ...
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0answers
29 views

Dectect White noise ACF - PACF Eviews

I found PACF and ACF like the following table . But, how can I decide whether there exists white noise? And what is white noise? If there is white noise, how can i build my best fit model with ...
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0answers
28 views

Interpretting arima xreg output in R

I have an interrupted time series consisting of 200 observations that I've cleaved into two subseries: a sub-series of 150 pre-interrupted observations, and a sub-series of 50 post-interrupted ...
2
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1answer
47 views

Fitting an ARIMA model with conflicting indicators

I have a time series data set to which I want to fit an ARIMA model. In looking at the plot of the data, it seems stationary, albeit perhaps marginally so. No trends, no seasonal effects, somewhat ...
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0answers
40 views

How to represent an ARIMA(p,d,q) with dlm package in R? [closed]

I've been using DLM package for modeling my timeseries in state-space format, and then use Kalman Filter to get better 2 step-ahead forecasts. Even though I've read the vignette and parts of their ...
0
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1answer
19 views

Best way to fit an ARIMA model when the values of the variables don't change

I have a time series with various features that record sensor data. It can be the case that the values are recorded although they did not change compared to the previous observation. Hence, the series ...
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1answer
82 views

forecast(method ='arima') ; auto.arima() function, how to avoid forecast not in line with history?

I am working on an alogorithm in R to automatize a monthly forecast calculation. I am using, among others, the forecast(method='arima') function from the forecast package to calculate forecast. It is ...
2
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1answer
73 views

How can a univariate seasonal time series be made normally distrubuted by Box-Cox transformation?

I'm trying to fit a sarima model on the univariate data with 180 points (periodicity=12). I use the auto.arima function in R. After fitting a model to the data, the only problem is the violation of ...
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0answers
56 views

ARIMA vs. Random Forest

We have some power load functions that of course are driven heavily by a workday rhythm that we need to forecast, and after some light research into the topic, I see that using ARIMA would seemingly ...
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0answers
23 views

Determining the optimal lookback length for an arima forecast

How can I determine the optimal lookback length for an arima forecast? ...
2
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1answer
41 views

Prediction intervals in ARIMAX accounting for forecast uncertainty in future $X$?

I have a problem with my SPSS software and ARIMAX forecasts. Consider a series $Y$ that depends on a different series $X$, which is not known in advance with certainty, but must be forecasted itself. ...
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28 views

Bivariate ARIMA model in Stata

I am having troubles fitting a bivariate ARIMA model in STATA. Is there such a capability at all? I can choose dependent and independent variables but once I set them to be mortality and alcohol ...
2
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1answer
73 views

Constraints on the Coefficients of a Seasonal ARIMA Model (Possible Software Bug ITSM)

I am attempting to fit a seasonal ARIMA models using ITSM software. The following is the model. ARIMA$(1,1,0)\times(1,1,0)_{12}$: $\phi(B) \Phi(B^{12}) = (1-\phi B)(1-\Phi B^{12})=1-\Phi ...
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0answers
43 views

Is this the wrong way to do cross-validation?

I am building an ARIMA model and did a grid search to find which values to use for my AR and MA components using the AIC criteria (this was using all of my data). The results are in this graphic: ...
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1answer
141 views

R Time Series Analysis forecast result always remains same

I am trying to do time series analysis in R. I have data time series data set like this. ...
4
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2answers
42 views

Which forecast way is better

I want to predict daily headcount in a given area. The area can be divided into several blocks. The blocks share very little similarity. The question is, if I'm only interested in total daily ...
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0answers
27 views

Best way to select parameters to SARIMAX model

I am trying to understand what is the best way to find the hyper-parameters for an SARIMAX timeseries model, this has 4 additional parameters (P-AR parameters,D-differences,Q-MA ...
2
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2answers
94 views

Which econometric models can be used to forecast security returns + ARIMA/GARCH questions

I'm trying to write an undergraduate thesis wherein I test the predictive power of a given econometric model on a given financial time series. I need some advice on how I should go about doing this. ...
2
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0answers
38 views

Why and when stationarity is achieved by decomposition rather than differencing in ARIMA model

I would like to understand relationships between variables by which cross-correlation function, that means what is the extent one variable influence the other one. ARMA model is used to fit two ...
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0answers
30 views

How to build separate time series forecasts model for each of 3k customers?

I have 3000 customers in my base and i want to forecast next 6 months revenue for each of these 3000 customers. Does that mean i have to build 3000 arima models 1 for each customer? I can build a ...
4
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1answer
34 views

Understanding fractional-differencing formula

I have a time series $y_t$ and I would like to model it as an ARFIMA (a.k.a. FARIMA) process. If $y_t$ is integrated of (fractional) order $d$, I would like to fractionally-difference it to make it ...
4
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1answer
63 views

Ljung-Box always significant for ARIMA models - what now?

Sorry in advance if this is too basic of a question - I've been struggling with this data set for almost a month and feel like I'm going in circles, and the more I Google the more confused I get. I ...
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1answer
46 views

How to fit an ARIMA model with seasonality in R? [closed]

I have a set of monthly data and detected seasonality. The ACF and PACF is shown below. How can I set c=(p,d,q) for non-seasonal part and c=(P,D,Q) for seasonal part based on the figures.
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1answer
112 views

What is the best filter/way for deseasonalizing quarterly data?

There are many deseasonalization techniques for deseasonalizing quarterly time series data: 1. Filter: Centered moving averages 2. Filter/way: automatic ARIMA selection using X-11-Auto , X-11 based ...