Results 21 to 30 of about 115 (106)
Sample correlations of infinite variance time series models: an empirical and theoretical study
International Journal of Stochastic Analysis, Volume 11, Issue 3, Page 255-282, 1998., 1998 When the elements of a stationary ergodic time series have finite variance the sample correlation function converges (with probability 1) to the theoretical correlation function. What happens in the case where the variance is infinite? In certain cases, the sample correlation function converges in probability to a constant, but not always.
Jason Cohen +2 more
wiley +1 more source
Peramalan curah hujan di Provinsi Aceh menggunakan metode Box-Jenkins
Majalah Ilmiah Matematika dan Statistika, 2023 Floods are one of the natural disasters that frequently occur in Indonesia, including in Aceh Province. Floods primarily occur when rainfall is intense, mainly in the rainy season.
Nurhafifah Nurhafifah +5 more
doaj +1 more source
The empirical TES methodology: modeling empirical time series
International Journal of Stochastic Analysis, Volume 10, Issue 4, Page 333-353, 1997., 1997 TES (Transform‐Expand‐Sample) is a versatile class of stochastic sequences defined via an autoregressive scheme with modulo‐1 reduction and additional transformations. The scope of TES encompasses a wide variety of sample path behaviors, which in turn give rise to autocorrelation functions with diverse functional forms ‐ monotone, oscillatory ...
Benjamin Melamed
wiley +1 more source
Quasi-maximum likelihood estimator of Laplace (1, 1) for GARCH models
Open Mathematics, 2017 This paper studies the quasi-maximum likelihood estimator (QMLE) for the generalized autoregressive conditional heteroscedastic (GARCH) model based on the Laplace (1,1) residuals.
Xuan Haiyan +3 more
doaj +1 more source
Geoestadística aplicada a series de tiempo autorregresivas: un estudio de simulación
Revista Integración, 2017 La geoestadística puede usarse como método de predicción de datos faltantes en series temporales. El procedimiento se basa en el estudio de la estructura de autocorrelación temporal de la serie de tiempo por medio de la función de variograma, que es ...
Ramón Giraldo +2 more
doaj +1 more source
Ingeniería y Ciencia, 2012 Muchas series de tiempo con tendencia y ciclos estacionales son exitosamente modeladas y pronosticadas usando el modelo airline de Box y Jenkins; sin embargo, la presencia de no linealidades en los datos son despreciadas por este modelo. En este artículo,
J D Velásquez, C J Franco
doaj +1 more source
Exponential inequalities for nonstationary Markov chains
Dependence Modeling, 2019 Exponential inequalities are main tools in machine learning theory. To prove exponential inequalities for non i.i.d random variables allows to extend many learning techniques to these variables.
Alquier Pierre +2 more
doaj +1 more source
Ingeniería y Ciencia, 2015 En este trabajo se identificó un modelo en series de tiempo para el control de la tasa de penetración (ROP) en un pozo de referencia denominado V∗∗∗ que pertenece al campo en desarrollo VEL que está ubicado en la cuenca del Valle del Magdalena Medio (VMM)
Henry Daniel Hernández Martínez +1 more
doaj +1 more source
Journal of Causal InferenceTime-dependent coarse structural nested mean models (coarse SNMMs) were developed to estimate treatment effects from longitudinal observational data. Coarse SNMMs estimate the combined effect of multiple treatment dosages and are thus useful to estimate ...
Lok Judith J.
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Statistical, machine learning, and deep learning models for COVID-19 forecasting in Kenya
Computational and Mathematical BiophysicsThis study aims to enhance coronavirus disease 2019 forecasting in Kenya by comparing the predictive performance of statistical, machine learning, and deep learning (DL) models for total cases, critical cases, severe cases, and total deaths, using data ...
Kiarie Joyce +4 more
doaj +1 more source