Results 111 to 120 of about 72,789 (297)

Density‐Valued ARMA Models by Spline Mixtures

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This paper proposes a novel framework for modeling time series of probability density functions by extending autoregressive moving average (ARMA) models to density‐valued data. The method is based on a transformation approach, wherein each density function on a compact domain [0,1]d$$ {\left[0,1\right]}^d $$ is approximated by a B‐spline ...
Yasumasa Matsuda, Rei Iwafuchi
wiley   +1 more source

A class of fractional order neural network systems with sector dead zones for synchronization

open access: yesNantong Daxue xuebao. Ziran kexue ban
Synchronization is examined for a class of fractional order neural network systems with sector dead zones and orders between 1 and 2. Through variable replacement, the synchronization problem for systems with orders in(1,2) is reformulated as one with ...
JIANG Wenfang;LIU Heng
doaj   +1 more source

Robust CDF‐Filtering of a Location Parameter

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania   +2 more
wiley   +1 more source

A Note on Local Polynomial Regression for Time Series in Banach Spaces

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This work extends local polynomial regression to Banach space‐valued time series for estimating smoothly varying means and their derivatives in non‐stationary data. The asymptotic properties of both the standard and bias‐reduced Jackknife estimators are analyzed under mild moment conditions, establishing their convergence rates.
Florian Heinrichs
wiley   +1 more source

Sequential Outlier Detection in Nonstationary Time Series

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT A novel method for sequential outlier detection in nonstationary time series is proposed. The method tests the null hypothesis of “no outlier” at each time point, addressing the multiple testing problem by bounding the error probability of successive tests, using extreme‐value theory. The asymptotic properties of the test statistic are studied
Florian Heinrichs   +2 more
wiley   +1 more source

Lipschitz functions of continuous functions [PDF]

open access: yesPacific Journal of Mathematics, 1953
Marx, Imanuel, Piranian, George
openaire   +3 more sources

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