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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One Step Ahead with a forecast horizon of 25

I have 288 data points of the Wolf's sunspot data for the years 1700 to 1987. I need to predict one step ahead forecasts for a forecast horizon of 25. I kept the last 25 data points of the time ...
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15 views

Is there a way to force seasonality from auto.arima [migrated]

With the forecast package, I have a time series that I would like ?auto.arima to automatically pick the orders but I would like ...
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1answer
31 views

Time Series forecasting with useful predictor variables

I am playing with time series data related to a issue ticketing system. The system logs all open tickets at any one point and my task is to predict what the volume of open tickets will be in 5,10,15 ...
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1answer
19 views

Standard errors `NaN` by `Arima` function in R

I'm working with a time series of 59 elements. I'm wondering why the R function, Arima, throws an NaN for the standard errors of ...
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18 views

Optim error training ARIMA model in R [duplicate]

I have the code below which trains ARIMA models for a range of order combinations. I'm getting the error below in the step training the ARIMA models. The code worked just fine with the ...
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14 views

How to write the equation for ARIMA(0,0,1)(1,0,0) with exogenous regressors?

How I should write the equation for this ARIMA(0,0,1)(1,0,0) based on this SPSS parameter output? What if it is an ARIMA (0,0,0) or ARIMA (1,0,0) with the same variables? The independent variables ...
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2answers
45 views

R auto.arima with intervention: intervention only affects one point

I have a model fitted with auto.arima, the model is ARIMA(0,1,0)x(0,1,0)[6] with seasonal period 6. The data is bi-monthly so there is an annual seasonality. There ...
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1answer
38 views

Fitting Methods in Arima

Could someone please explain the differences between the 3 fitting methods, method = c("CSS-ML", "ML", "CSS"), in Arima? If I run the code below I get an error message, but if I specify method="ML" ...
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31 views

ARMA when ARIMA should be used

(Note: I am taking a first course in time series -- correct me where I am wrong.) What happens when we fit an ARMA model to a time series when a differenced model (ARIMA with nontrivial $d$), should ...
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17 views

Reg-Arima fitted estimates more flexible than forecast

I am fitting a regression model with ARMA errors, and comparing its fitted and forecasted values with a linear regression. I am wondering why a reg-ARMA appears to have a much better fitted estimate ...
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35 views

More effective seasonal adjustment to time series data?

I am trying to predict surface temperature using solar energy. I have 3650 daily averages for both variables. The plots of both are below: I attempt to seasonally adjust with a periodic ...
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17 views

How do you create an ARIMA model with year wise regressors?

I am trying to understand how discontinuations in products have an effect on sales volume. I have a sales variable and information on product discontinuation sales volume by month and year. For ...
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1answer
31 views

How is the first residual calculated in a fitted AR(1) model?

I am trying to figure out how the first residual is calculated in an AR(1) model. It's easy to generate all of the other residuals, but I have no idea how r calculates the first one. Here is an ...
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1answer
28 views

Selecting ARIMA Order using Rolling Forecast

I'm wondering if a rolling forecast technique like the ones mentioned in Rob Hyndman's blogs, and the example below, could be used to select the order for an ARIMA model? In the examples I've looked ...
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1answer
29 views

Historical data appears seasonal, but forecasts from auto.arima are linear

I am surprised how often the auto.arima function from the "forecast" package in R returns straight linear forecasts when there appears to be fairly strong ...
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2answers
432 views

Is every ARIMA(1,1,0) model equivalent to an AR(2) model?

Assume I have a time series $ x_t $ that I want to fit using an ARIMA(1,1,0) model of the form: $ \Delta x_t = \alpha \Delta x_{t-1} + w_t $ This could be rewritten as: $ x_t - x_{t-1} = ...
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1answer
26 views

Rolling Forecast Re-training Step Concept

I'm trying to understand the steps in Rob Hyndman's Multi-step forecasts without re-estimation example below. I'm wondering what the purpose is of ...
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1answer
12 views

Interpretation of external regression coefficient in linear regression with ARMA errors

I am fitting a linear regression model $y_t = b\times x_t + u_t$ with ARMA errors $u_t$. Is the interpretation of $b$ the same as in usual linear regression?
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5 views

Forecasting Call Center Wait time with Unknown Staff Levels

I am trying to forecast the median wait time each hour for a customer to get served in a call center. I know the median wait times each hour and the number of customers who called in each hour ...
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1answer
35 views

Constructing Deterministic Trend and AR(1) and Forecasting in R

I am trying to implement/generate a process using arima.sim like this: $Y_t = a + b*t + \epsilon_t$, where $\epsilon_t = \phi\epsilon_{t-1}+\gamma_t$ a AR(1) ...
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1answer
28 views

auto.arima Not Minimizing AIC

I simulated a MA(3) process using: ...
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9 views

`auto.arima` warning message: NaNs produced (in coefficient variance matrix) [migrated]

I got a warning from function auto.arima in "forecast" package in R, which said: ...
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1answer
26 views

Question about rolling forecast horizon

I'm trying to understand how the rolling forecast example below from Rob Hyndman's blog works. In the final line of the for loop, is ...
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1answer
39 views

Are rolling forecasts more accurate that full-sample forecasts?

I compared the auto.arima forecast checkts below to the rolling forecast fc and noticed ...
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1answer
22 views

Very different prediction intervals from ARIMA models where MA order differs by 1

I have fit an ARIMA model to a time series with function auto.arima from "forecast" package in R. I wanted to check prediction intervals for robustness by changing ...
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7 views

Rolling Hourly Forecast Error [migrated]

When I try to run the code below, I'm getting the following error: Error in Ops.POSIXt(driftmod$coeff[2], time(x)) : '*' not defined for "POSIXt" objects I ...
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1answer
47 views

How to set the prediction range of ARIMA model in R

I am new to R and statistics. I have a problem related to the prediction: I am not able to plot the real value together with the predicted value. PROBLEM: I want to feed first 16 values into the ...
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1answer
51 views

How to identify best Model for univariate time series data?

I have a time series data- 53.97 63.32 57.06 60.27 69.46 75.08 78.31 73.28 85.84 69.34 62.57 60.11 55.63 47.29 61.22 58.46 66.26 59.71 51.12 39.36 51.89 ...
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10 views

Detecting Frequency in Noisy Data

I have some very noisy data that seems like it might have a frequency to it. I'm trying to build a model with the data, like the example code below. So I've been experimenting with fourier series ...
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12 views

ARIMA practical application to Forex

Can we apply ARIMA for forex forecasts using R on Azure machine learning? If yes, how?Is it possible to apply machine learning for algorithmic trading by using Microsoft's Azure or Google's API for ...
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28 views

Help discussing stationarity using correlograms? ARMA/ARIMA modelling

I am currently trying to understand how to use correlograms to examine stationarity and analysis the appropriate models. Please can you advice, below I have included my ACFs and PACFs, and I am trying ...
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1answer
55 views

How to create a random walk model using {forecast} R package

I have a good understanding of ARIMA models but I've always found significant spikes in ACFs and PACFs that gave me the appropriate AR and MA parameters. Now I'm dealing with a series that is more ...
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23 views

ARIMA with xreg - how to illustrate and/or explain the findings in plain English?

I have time series data on drug trade revenue in a city over a four-month period (DP). I also have data on police crackdowns and raids in the same period, in the same city (IV). I want to see if the ...
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80 views

Principal components analysis: relationship between first and second principal component

I'm really struggling with understanding the idea of Principal Component Analysis and would appreciate any help. We have a m multivariate input time series $ \begin{align} X_{t} &= ...
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1answer
24 views

How does R calculate parameters of MA model?

How does R calculate parameters of MA model? What is the algorithm? In wikipedia, it is said Fitting the MA estimates is more complicated than with autoregressive models (AR models) because the ...
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26 views

Mimicking seasonaldummy with fourier in Arima model

I'm trying to forecast data that has an hourly and weekly pattern. The model I made using predictors created using seasonaldummy does a nice job of picking up the hourly weekly pattern, but it takes ...
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1answer
30 views

Measure of Central Tendancy in ARIMA?

I know very little about the ARIMA - the AutoRegressive Integrated Moving Average - model but I am interested in what type of central tendency is represented by "average". Is it simply the mean? If ...
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1answer
22 views

Arima Model with weekday dummy variables Forecast

I'm trying to create an Arima model and forecast it ahead the next 20 hours using the code and data below. When I look at the median of df$tri for each hour and broken down by day of the week, each ...
5
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1answer
64 views

Is it valid to use an ARMAX model for TV Attribution?

Suppose I have a website which has some baseline hourly traffic. I also run TV advertising intermittently which drives up my web traffic. I want to determine how much effect my TV advertising is ...
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1answer
47 views

How to compute estimate for the first time series value using ARIMA model?

I modeled a univariate time series in R using the Arima command. One can obtain fitted values for the original series using this command by applying the function ...
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1answer
21 views

How to handle interruptions (0 values) over a certain period in time series analysis?

Is there a way that I can combine two models for time series? I am trying to predict the production of tomatoes per week per $m^2$ (black line), based on light (orange) and temperature (magenta). At ...
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22 views

Why can't I put Constant in xreg to fit Arima model

I am new to Arima model. I am playing with a weekly incidence data set. I want to fit an Arima model. The covariates that I want to use is as follow ...
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10 views

Length of Arima Training data

I'm trying to forecast 10 hours ahead using an Arima model. I was wondering what a good rule of thumb is for the length of training data required. If I use too long a training set I wind up with a ...
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21 views

Arima Model Fitting when Acf and Pacf are Sinusoidal

I am trying to follow the Arima Modelling Procedure outlined in Rob Hyndman's online text book, (link below) https://www.otexts.org/fpp/8/7 I'm using the data below. I'm confused about step 4 ...
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20 views

Lag length for the Ljung-Box test

I have an ARIMA model applied on hourly data: Arima.fit2 <- Arima(tsTrain, order=c(17,1,0)) The length of my training set is 60 hours. In the end I plan to ...
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37 views

Time series : what model to choose

I'm still a beginner in statistics, and would like to ask for your help. I'm studying the effects of several variables divided into two groups (climatic, agricultural) on biological variables. I have ...
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1answer
41 views

What-if analysis using a fitted regression with ARMA errors

Using linear regression as an equation for prediction is straightforward with, $$ Y_i = \beta_0 + \beta_1 X_i. $$ Once the betas are estimated I can insert different values of $X$ to use as a ...
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1answer
23 views

Predicting point forecast using Random walk model coefficients

I have created a random walk model ARIMA(0,1,0) in R. The coefficients and R output is as shown below: ...
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1answer
25 views

Proper definition of AR()-ARCH() time series model

This is how I would define it, if anyone has any objections please let me know! AR(m)-ARCH(m) time series is an ARCH(m) process in which the variance at time t is conditional on the previous m times ...
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1answer
32 views

Is there any way to account for variable interaction in R's auto.arima?

I'm using the auto.arima function in R's forecast package to build an ARIMA model with external regressors. I have a ...