Results 21 to 30 of about 1,135 (106)

Pemodelan angka kematian bayi di Indonesia menggunakan Geographically Weighted Regression (GWR) dan Mixed Geographically Weighted Regression (MGWR)

open access: yesMajalah 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

open access: yesInternational 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

Volatility filtering in estimation of kurtosis (and variance)

open access: yesDependence Modeling, 2019
The kurtosis of the distribution of financial returns characterized by high volatility persistence and thick tails is notoriously difficult to estimate precisely.
Anatolyev Stanislav
doaj   +1 more source

Sample correlations of infinite variance time series models: an empirical and theoretical study

open access: yesInternational 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

Prediction of time series by statistical learning: general losses and fast rates

open access: yesDependence Modeling, 2013
We establish rates of convergences in statistical learning for time series forecasting. Using the PAC-Bayesian approach, slow rates of convergence √ d/n for the Gibbs estimator under the absolute loss were given in a previous work [7], where n is the ...
Alquier Pierre   +2 more
doaj   +1 more source

Peramalan curah hujan di Provinsi Aceh menggunakan metode Box-Jenkins

open access: yesMajalah 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

open access: yesInternational 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

Functional generalized autoregressive conditional heteroskedasticity [PDF]

open access: yes, 2015
Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the focus of research
Aue, Alexander   +2 more
core   +2 more sources

Time series properties of the class of generalized first-order autoregressive processes with moving average errors [PDF]

open access: yes, 2009
A new class of time series models known as Generalized Autoregressive of order one with first-order moving average errors has been introduced in order to reveal some hidden features of certain time series data.
Peiris, Shelton, Shitan, Mahendran
core   +1 more source

Exponential inequalities for nonstationary Markov chains

open access: yesDependence 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

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