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Test de raíz unitaria de Phillips-Perron (PP)×Modelo ARIMA (Autoregressive Integrated Moving Average)×
CampoEconometríaEconometría
FamiliaRegression modelRegression model
Año de origen19882015
Autor originalPeter C. B. Phillips & Pierre PerronBox & Jenkins (Box-Jenkins methodology)
TipoUnit-root test for stationarityUnivariate time-series model
Fuente seminalPhillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021
AliasPP test, Phillips-Perron unit root test, Phillips-Perron birim kök testiBox-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
Relacionados45
ResumenThe Phillips-Perron test, proposed by Peter Phillips and Pierre Perron in 1988, tests for a unit root in a time series, like the Augmented Dickey-Fuller test, but corrects for autocorrelation and heteroskedasticity in the errors non-parametrically rather than by adding lagged differences. It runs a simple Dickey-Fuller regression and then adjusts the test statistic using a long-run variance estimate, so the practitioner need not choose a lag length for the regression itself.ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).
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ScholarGateComparar métodos: Phillips-Perron Test · ARIMA. Recuperado el 2026-06-17 de https://scholargate.app/es/compare