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ARIMAmodelbased decomposition of time series in R
The tsdecomp R package  The uroot R package is back
 Airline prices database

An application of OpenMP and Graphics Processing Units parallel threads
Numerical distribution functions of unit root tests
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Category Archives: time series
Testing for seasonal stability
Canova and Hansen test statistic
Seasonal patterns are common in many time series data (e.g. macroeconomic or meteorological data). One of the issues to be analyzed when working with seasonal data is whether the seasonal pattern remains relatively stable over the sample period or whether … Continue reading
Does a seasonal ARIMA model involve seasonality?
The question posed in the title may seem a tautology, but it’s not. If an ARIMA model (chosen by any manual or automated procedure) contains lags of seasonal order, it does not necessarily mean that there is a relevant seasonal … Continue reading
$$F$$test statistic in autoregressive models
Under the framework of the classical linear regression model, the ordinary least squares (OLS) estimator has good properties: it is unbiased, has minimum variance compared to other linear estimators and the usual test statistics follow common distributions. An autoregressive model … Continue reading
Posted in regression model, simulations, time series
Tagged autoregressive model, bootstrap, Ftest
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Variations on a maximum likelihood procedure
Structural time series models are a appealing frame work for time series modelling since components such as the trend or the seasonal are explicitly modelled. Besides, both deterministic components or stochastic components can be captured by these models. At first … Continue reading
Posted in applications, R, time series
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Unit root tests: an endless source of research articles
Note: The following are BibTex and pdf files containing the references cited in this post: bib.bibreferences.pdf. As witnessed by the number of journal articles published in this area, unit root tests have been extensively studied. Here, I will review some … Continue reading