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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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auto.arima manage dummy variables in xreg argument?

Im using auto.arima to forecast. Im including some dummy variables in the "xreg" argument to manage break points. But i read that if auto.arima makes a first difference on "y", it also do a first ...
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8 views

level shift outlier model

Does somebody happen to know how to calculate the forecast with the LS formula since it got denominator? I got confused because of that. Here's the model I've been using for the forecast.
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28 views

Closeness of two ARMA models

Given two ARMA models, how close will their predictions be? Specializing to the case of ARMA(1,1), if a time series follows an ARMA process ...
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1answer
33 views

Determine AR term from PACF plot

I have the a time series data, the acf and pacf for which have been displayed below: I get that MA term is 1. But I'm confused about AR term since it is geometrically decaying from 7th lag. Do I need ...
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19 views

Time series model fitting for a series that is not being stationary

I've been trying to fit a model to a series that is very hard to make stationary. this is the series ...
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2answers
49 views

Econometric models? [on hold]

I'm confused about econometrics models. Let's say I used a daily stock market index for 5 years, and I want to see how oil price affect the stock markets return , let's assume ( as a fact ) that oil ...
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17 views

Intervention Analysis Forecasting [on hold]

I am using intervention model in R. Say, the time series data is composed of 72 observations in quarterly basis, named as data. Then, a step intervention in ...
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0answers
18 views

Differencing causes negative predictions

I have a non - stationary time series sequence which is based on counts. To convert the sequence into stationary I applied differencing, which converted the sequence into stationary but the sequence ...
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7answers
3k views

What's the point of time series analysis?

What is the point of time series analysis? There are plenty of other statistical methods, such as regression and machine learning, that have obvious use cases: regression can provide information on ...
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6 views

How to inverse powertransformations and differencing after creating a SARIMA model in python?

I am creating a SARIMA-Model in python. I log-transform my original data, take 1st difference and 1st seasonal difference. my1SeasonalDiff is then stationary data. ...
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0answers
10 views

Cross validation using external regressors

I'm quite new to forecasting. I'm trying to use the tsCV() command for an ARIMA model with external regressors. I'm failing in writing the right function to use in the tsCV() command My time series ...
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0answers
15 views

Variance of an ARMA process

I'm trying to obtain the variance function of an ARMA process and I'm in doubt if (any or all of) the following (due to the properties of a white noise process) is true: ${\operatorname{cov} \left( {{...
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17 views

first order differential data is the white noise, Can we predict in this case?

if the time series is non stationary and the first difference makes it stationary . but the ACF and PACF shows the first order differential data is white noise,The question is, can ARIMA models be ...
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24 views

how to merge two different time series in pandas (with different variables) [closed]

How can I normalize mulitvariate timeseries categorical data for use with ARIMA models like varmax? This question is not about the programmatic means of data wrangling, but rather about what exactly ...
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0answers
13 views

Arima vs HoltWinters

I am currently performing some sales forecasting and I am debating between an ARIMA model, using the auto.arima function in R, or a HoltWinters model, using the HoltWinters function in R. What are ...
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9 views

sarima coefficients written in equation [duplicate]

ARIMA(1,0,0)(1,1,0)[12] with drift Coefficients: ar1 sar1 drift 0.5158 -0.5307 -0.0043 s.e. 0.0696 0.0722 0.0059 sigma^2 estimated as 0.4256: log likelihood=-155.35 ...
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7 views

What does a negative denominator term mean in an SPSS ARIMA transfer function?

From the discussion here: Transfer function in forecasting models - interpretation I have the impression that a negative denominator coefficient for a predictor variable in a transfer function would ...
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0answers
10 views

Is the Dickey-Fuller tests is a seasonality test as it tests the existence of the unit root?

Knowing that the "Dickey-Fuller tests" tests if the times series is stationary or not by testing the existence of the unit root, after fitting the time series to AR(1) process. Does "Dickey-Fuller ...
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14 views

More AR lags means more persistence?

Suppose that $x_t$ is an ARMA(p,q) stochastic variable and that $y_t$ is another stochastic process that satisfies $$ y_t = \frac{1}{(1-\rho_1 L)\cdots(1-\rho_n L)} x_t, $$ where $L$ is the lag ...
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16 views

What is the calibration performance of the model?

I have a hydrologic model which uses rainfall data and transform into discharge data. I have calibrated the model for the period 2010-2012 with observed data. Model simulation data somewhat differs ...
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26 views

Choosing a model

I am working on a sales forecast right now and I have created 4 models but I am unsure which one to use. I have 17 Quarters of data(4 Full years + 1 QTR) and I am only looking to forecast 2 quarters ...
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1answer
17 views

What is the number of iterations used to estimate the ARMA coefficient

If we are using the LSE "least square error" equation for getting the AR and MA terms: by getting the LSE in function of the coefficients and differencing it then equating it to zero.This yields ...
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16 views

TimeSeries Analysis for a dataset gave different result for a calculared subset of it

I am trying to understand timeseries analysis. I ran ARIMA model for same, the values i got were... p,i,q =(7, 1, 1) Now i created a subset from this dataset by applying certain external filters ...
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11 views

Confidence or prediction interval for in-sample prediction?

I'm trying to make a plot of the uncertainty interval of in-sample prediction ...
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0answers
23 views

Time series analysis where computing the exact value is possible (but expensive)

I have a stationary time series where it is actually possible for me to compute the exact next value. These computations are very expensive, and to speed things up I want to employ following scheme: ...
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1answer
53 views

SARIMA model with SARIMA residuals

I currently about to work my way into the time series model a former colleague om mine implemented: it is a SARIMA model (seasonal ARIMA) with SARIMA residuals. First I want to give a brief ...
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43 views

Accuracy metric for comparing Time Series models?

I'm writing a blog post on forecasting time series with autoregression. In it, I compare the performance of SLR, ARIMA, and SARIMAX on forecasting the number of Home Sales in Seattle (see below). All ...
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33 views

OLS with AutoRegressive Errors on Non-Stationarised Data

I'm working with some time series data (n=40) and trying to fit an OLS with AutoRegressive Errors to model the relationship between my dependent variable and a couple of predictors over time. I'm ...
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1answer
21 views

How to interpret a seasonal ARIMA model?

I have an auto.arima model output with ARIMA(000)(110)[4] with sigma^2=0.005, so I assume the model fits well the data. But I'm trying to understand the model itself... If I did all the maths ...
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27 views

Interpreting coefficients from SPSS ARIMA Model Parameter Table

I'm trying to figure out how to make a prediction equation from the coefficients of an SPSS ARIMA model parameter table. Based on what I understand of the backshift operator notation, I've written ...
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1answer
25 views

What is the difference between the estimation technique used for `ARIMA()` and for `lm()` in R?

Does anyone have an idea on this? In R, for arima(), I do the following: arima(ts.GDP, order = c(3,0,0), seasonal = c(0,0,0)) ...
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1answer
40 views

ARIMA Model Stage 3 (Residual Diagnostic) - Is the residual a white noise?

Work Done: I have a monthly time-series data (Consumer Price Index) from 1976 to 1993. I performed first differencing and log transformation to detrend it, also, Augmented Dickey-Fuller Test has ...
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25 views

Why is WAPE always lower than MAPE [closed]

I'm running a time series forecast using ARIMA. I am using the following calculations for MAPE and WAPE. I expected to get a higher WAPE than MAPE because I'm not removing the zero actuals from my ...
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15 views

Difference of Forecast ,predictors and regression residuals in auto.arima

I am forecasting daily electricity demand using daily temperature as a predictor variable in r using auto.arima and got (2,1,2)(2,0,0)7 errors. The link https://otexts.org/fpp2/dynamic.html suggest ...
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1answer
57 views

ARIMA Time series analysis forecasting [closed]

I am having a small project on Time series analysis for that I have hourly sales data for that I need to forecast hourly sales for the next 1 month, i.e around next 720 hours I am exploring ARIMA for ...
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19 views

ARIMA Time series analysis

Hi I am having a small project on Time series analysis for that I have hourly sales data for that I need to forecast hourly sales for the next 1 month i.e around next 720 hours I am exploring ARIMA ...
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0answers
38 views

sarima model with additional regressors

I have fitted a SARIMA model for daily data with 5 regressor variables. In addition, I used Fourier terms to capture the seasonal patterns in the model according to the prof. Hyndman post on daily ...
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43 views

ARMA-GARCH model with t-distributed errors

I've estimated an ARMA(1,2)-GARCH(1,1) model fitted on financial data. It is very satisfactory in modeling the autocorrelation and the volatility in my data, however, the qq-plot empirical quantiles ...
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17 views

ARIMA Cross-Validation with Range of Orders

I have been working my way through Hyndman's Forecasting: Principles & Practice and tried to replicate Table 8.2, but instead of manually passing Arima() the ...
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1answer
49 views

Can I apply ARIMA(p, d, q) model to testing dataset and make forecast with the testing dataset? Just like the scenario of regression model?

After I fit a sarima model with some historical sales data (for example A dataset), I get coefficients of sma1 and ar1. And I'd like to apply this model to current sales data (for example B dataset) ...
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1answer
31 views

What is ARMA error in time series?

I heard a term "ARMA ERROR" in BATS and TBATS. How it helps in time series forecasting.
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31 views

I have a time series dataset. I am looking to answer 2 forecast questions:

(1) At any given time 't' the machine is upstate/downstate (logistic) (2) Forecasting total downtime of the machine in the coming 10 weeks? The dataset looks like this where Count is no of downtimes ...
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2answers
46 views

Derivation of the ARMA model as acombination of the AR and MA models

On the Wikipedia article on the ARMA model, its derivation is simplified as a combination of the AR and MA models: AR $$ X_t = c + \sum_{i=1}^p \varphi_i X_{t-i} + \varepsilon_t $$ MA $$ X_t = ...
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39 views

How to forecast a time series in R with ts() [closed]

For June 2009 - June 2018, I have prices for product to be delivered that month if bought on the date on the left most column. This below is an excerpt to show the format. The 1-5 and so on r between ...
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0answers
27 views

divergence of beta estimates between OLS and regression with ARIMA error

I have physiological time-series data: ~60k observations per channel, ~100 Hz sampling. I will model individual channels with ~20 regressors. Under OLS, given temporal autocorrelation in the data, ...
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33 views

auto.arima() and manual search gives different p & q values

Hello, I have a non-stationary time series (population data) with 66 observations. Attached png file contains the acf and pacf plot for differenced (d=2) series. (1) From that I assumed p=1 & q=1 (...
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30 views

I am getting error in arima function of R forecast package for both methods, CSS and ML

Given below are the errors, dataset and code snippet. What do I need to do to run the model? For CSS the error is Error in solve.default(res$hessian * n.used) : Lapack routine dgesv: system ...
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1answer
88 views

What's the definition of “Dynamic Regression Models”?

I am trying to learn about Dynamic Regression models. However, the sources on the topic is (relatively) few compared to other TS topics, and so I cannot really get a grasp of where to start. I really ...
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20 views

Compare forecast interval between ARIMA and ARIMA/GARCH

I tried to compute parameters of ARIMA/GARCH in two step. The first one is to build ARIMA and then fit GARCH using iid Gaussian MLE estimation. The second one is to construct ARIMA/GARCH ...
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1answer
42 views

how can I make ARIMA more robust to outliers?

I have a very noisy time series like this and I forcast future values with auto.arima from the forecast package in R: ...