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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7 views

Cross-validating the tbats/bats function in forecast

Is there a way to cross validate the tbats/bats function in the forecast package in R? I have been trying to get CV weighted parameters which then I can pass to a function for revised estimates. ...
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1answer
22 views

Forecasting: Turn a basic formula to an ARIMA model

What ARIMA model best represents a formula like this one. I thought that an arima(0,0,0)(1,1,0) or arima(0,0,0)(2,1,0) Would do the trick. But not. Any ...
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1answer
17 views

Forecasting with no seasonality

I have a set of data, let's say average weight of employees, captured every month over a period of 5 years (2010 - 2014). I cannot find a seasonality trend in the data over these years. Also, I have ...
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10 views

Prerequisites for time series and ARIMA

I am working on forecasting sales for 2016. The details of the problem is: 2014 - sales happened only between Jan-Apr 2015 - Sales happened only between Jan-Apr The sales in rest 8 months of the ...
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10 views

Which time series model to use?

Hi I have a large data set of objects, each containing a list of the same attributes. The data is arranged in a time series so that the value for an attribute for an object is indexed by its time. ...
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21 views

linear regression with autoregressive errors ~ARMA(1,0)(2,1)[12]

I am fitting monthly data that are expected to be auto-regressive (streamflow), but I want to include other independent variables (in my case it is a multivariate regression, with about 4 variables). ...
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19 views

Transfer function of pure ARMA time series model

Is it theoretically justifiable to calculate/use the transfer function of a pure ARMA model? I would like to be able to use the transfer function representation to put the state equations into their ...
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28 views

I want to know the AR and MA value for the following asap [on hold]

acf I WANT TO KNOW THE AR AND MA VALUE FOR THE FOLLOWING ACF AND PACF VALUES. PLEASE HELP ME.
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1answer
38 views

Modeling Time-Series with a lower bound

I am trying to fit a model to a time series that has a lower bound (at around -150). Using an ARIMA model, running simulations often leads to the time series hitting (and going underneath) this lower ...
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29 views

R: Time series forecasting alternatives to ARIMA [on hold]

I was using WEKA to perform time series forecasting based on lagged variables and machine learning algorithms: Time Series Analysis and Forecasting with Weka I am trying now to do something similar ...
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8 views
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16 views

ARIMA Simulation in R does not model data well

I have a time series that I wish to model with an ARIMA model in R. I computed the ARIMA model like so: arimaModel = arima(data, order = c(5,0,1)) When plotting ...
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1answer
36 views

How to compare ARIMA model in R to actual observations used to create the model?

I've been using the R forecast package's auto.arima() function to fit an ARIMA model to my time series data. I want to see how good of a fit the ARIMA model is to my original data. I hope to plot my ...
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19 views

ARIMA Model for forecast of wind speed

I'm trying to forecast the wind speed in order to predict the energy production of a wind tower. I wanted to use an ARIMA model to do that, i have data from every single minute during 1 year. So, i ...
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1answer
15 views

Interpolation model to estimate missing analytics

We have about 7 months of partially (30%) missing web analytics, that is apparently missing at random across all segmentations. We need to estimate the missing data to correctly compare current and ...
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2answers
54 views

Seasonal arima forecast equation

I need to compute a seasonal arima model, and make forecasts about vehicular traffic. My idea is to compute the model with R, and use the AR and MA coefficients in another application to predict ...
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18 views

Compare distributions in time series

I have a time series (weekly sales data), on which i have made an intervention analysis (to be specific a VARIMAX). The intervention (increased opening hours) ended out being insignificant. But what i ...
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15 views

R: Arima Model that only considers the previous 12 and 24 months for a given month

I have a time series that i want to do a model ARIMA (0,0,0) ((1,2),1,0) that 1 and 2 refers to month 12 and month 24. But the arima function does not allow me to do this ...
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1answer
86 views

Test of significance for a nonlinear trend in time series analyses, ARIMA

I have water temperature data consisting of monthly means for 20 years. As one would expect there is a definite seasonal/cyclical pattern. I wish to model the time series data by fitting an ARIMA ...
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13 views

Attributing effect of independent variables on time series data

Consider a response variable, say, sales of a company. This variable is time series data (confirmed by using ACF and PACF plots). The sales depend on other variables such as price of the product, ...
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1answer
42 views

How to identify relationship between response time series(Yt) & input time series(Xt) only in terms of Yt-1 & Xt?

I have a response time series(Y) & Input time series Xt & Zt. My only objective is to identify functional form Yt=f(Yt-1,Xt,Zt) where f(Yt-1,Xt,Zt) contains only lags of Yt , Xt & Zt as ...
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1answer
36 views

time series forecasting using auto.arima and exponential smoothing

I am working with workers’ remittance quarterly data for Bangladesh. Here I am doing time series forecasting using R. I am applying auto.arima model and exponential smoothing model. I want to compare ...
2
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1answer
61 views

Modelling time varying volatility when GARCH(1,1) coefficients sum to value greater one

First of all I have to admit that I am not a time-series expert so any help is highly appreciated. I have a financial time-series (a fixed income total return index measured on a weekly basis) for ...
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0answers
22 views

Getting exactly same forecasted values in auto arima [duplicate]

I am using auto.arima from forecast package for time series. The auto.arima selects best ...
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23 views

Interpreting a SARIMA model in SPSS - when is the model “good” enough for Interrupted Time Series

I am trying to analyse time trend data across a 10 year period (monthly) using SPSS, to do an interrupted time series analysis. I am not sure however, when a seasonal ARIMA model is "good enough". For ...
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1answer
29 views

How to check the residuals of a ARIMA-ARCH model?

Lets say we have a AR(1)-ARCH(1) time series model and we want to check the residuals for Ljung-Box. If the residuals of the model is Fit@residuals (using ...
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1answer
68 views

Reproducing Pankratz's ARIMA models for U.S. savings rate

I'm wondering if anyone has been able to reproduce the U.S. savings rate models in Pankratz's "Forecasting with Dynamic Regression Models"? If you google: pankratz table-1.6 The first link for me ...
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1answer
36 views

Volatility clustering test in Stata, time frame issues

I tested AAPL for ARCH effects using Stata with two different datasets (one was a subset of the other) and I obtained significant arch effects in one subset but not in the whole dataset. I would ...
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1answer
34 views

How are the weights set in the AR and MA?

I am studying ARIMA models and trying to get a grip of the concept. But I cant seem to find anyone motivating the values on the weights. Consider the following AR(2) model below, $Y_{t} = \mu + ...
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1answer
29 views

Forecasting a time series with conditional variance (heteroscedasticity) using Arima

I want to forecast a time series and have reason to believe that there are heteroscedastic errors/variance, which could be modelled with GARCH. However, I am not really interested in ...
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2answers
142 views

Forecasting: Is correct to say “If the time series is non-stationary” don't use ARIMA models?

In case I dont want to "pre-process" the time series. I do a unit root test, and if it gives that is a non-stationary time series, then I will stay away from ARIMA models. Is this correct?
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1answer
85 views

Linear regression with ARIMA errors variables selection

I have constructed linear regression model with ARIMA errors. Here is an output: Standard error of my IV coefficient seems to be very large compared to the coefficient itself. Can I conclude that ...
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1answer
40 views

Diferencing an autoregressive model

By differencing an AR(1) Model could we get an MA(1)? I mean $Y_t = U + Y_{t-1} + e_t$ $\Delta Y_t = Y_t - Y_{t-1} = U + E_t = U + E_t + 0 * E_{t-1}$ >> Meaning MA(1) ?
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41 views

Constructing 95% confidence intervals of coefficients in ARIMA model

For the recurrence relation below I simulated it in R with arima.sim and used arima.sim(data, order=c(2,0,2)) to estimate the coefficients. $x_t = x_{t-1} - \frac 13 x_{t-2} + w_t + \frac 14 ...
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18 views

Mean of Empirical Auto-Covariance

Chris Chatfield's "The Analysis of Time Series: An Introduction" 6th ed, gives the mean of the empirical auto-covariance as: E(r_k)=-1/N where E is the expectation r_k is the empirical ...
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44 views

How to write ar & ma terms in dynamic regression/arimax in terms of actual predictors?

I have done Arimax with response series Y as sales/demand & a set of input series on time series data at monthly level. The estimates from the arimax model is as shown below. I want to now ...
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2answers
77 views

GARCH forecasting in R: constant mean forecast!

I'm trying to forecast a time series of a stock option using ARMA-GARCH modelling in R. First I determine the ARMA order using AIC and I found (0,1) to be the best one. But when I run ...
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1answer
42 views

Difference time series and then minus the mean of the differenced series within Arima

This question is similar to the following question in the sense I am currently doing the differencing and mean removal of the time series outside the Arima function ...
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0answers
26 views

Why does the upper prediction interval region gets larger than lower prediction interval when data are transformed?

I present here two examples one with transformed data and the other without any transformation. In the transformed data case, the upper interval gets enormous large, whereas not in the untransformed ...
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45 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
106 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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0answers
19 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 ...
2
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0answers
29 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 ...
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0answers
33 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). ...
2
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0answers
16 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
26 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
50 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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56 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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41 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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24 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 ...