Results 21 to 30 of about 211 (152)
Introducing model uncertainty by moving blocks bootstrap [PDF]
, 2006 62M10, 62F40, sieve bootstrap, klockwise bootstrap, prediction, time series, model uncertainty,
Daniel Peña +7 more
core +1 more source
Majalah Ilmiah Matematika dan Statistika, 2022 The Infant Mortality Rate (IMR) is fundamental indicator that reflects the health status in the surrounding community. The Infant Mortality Rate is still categorized as high in Indonesia.
Muhammad Marizal +1 more
doaj +1 more source
Parallelization algorithms for modeling ARM processes
International Journal of Stochastic Analysis, Volume 13, Issue 4, Page 393-410, 2000., 2000 AutoRegressive Modular (ARM) processes are a new class of nonlinear stochastic processes, which can accurately model a large class of stochastic processes, by capturing the empirical distribution and autocorrelation function simultaneously. Given an empirical sample path, the ARM modeling procedure consists of two steps: a global search for locating ...
Benjamin Melamed, Santokh Singh
wiley +1 more source
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
Bayesian prediction in threshold autoregressive models with exponential white noise [PDF]
, 2004 Threshold model, Bayesian prediction, Gibbs sampler, 62CF15, 62M10, 62M20,
Isabel Pereira +3 more
core +1 more source
Bootstrap tests for nonparametric comparison of regression curves with dependent errors [PDF]
, 2007 Hypothesis testing, Regression models, Nonparametric estimators, Dependent data, 62G08, 62G09, 62G10, 62M10,
W. González-Manteiga +3 more
core +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