Results 51 to 60 of about 2,478 (171)

On Metric Choice in Dimension Reduction for Fréchet Regression

International Statistical Review, EarlyView.
Summary Fréchet regression is becoming a mainstay in modern data analysis for analysing non‐traditional data types belonging to general metric spaces. This novel regression method is especially useful in the analysis of complex health data such as continuous monitoring and imaging data.
Abdul‐Nasah Soale, Congli Ma, Siyu Chen, Obed Koomson   +3 more
wiley   +1 more source

Density‐Valued ARMA Models by Spline Mixtures

Journal 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

Nonlinear asymptotic stability in $L^\infty $ for Lipschitz solutions to scalar conservation laws

Comptes Rendus. Mathématique
In this note, we show nonlinear stability in $L^\infty $ for Lipschitz solutions to genuinely nonlinear, multi-dimensional scalar conservation laws. As an application, we are able to compute algebraic decay rates of the $L^\infty $ norm of perturbations ...
Golding, William
doaj   +1 more source

Robust Estimation and Inference for Time‐Varying Unconditional Volatility

Journal of Time Series Analysis, EarlyView.
ABSTRACT We derive a general and robust estimator of a large class of parametric specifications of time‐varying unconditional volatility of financial returns, both univariate and multivariate, and establish the Consistency and Asymptotic Normality (CAN) of the estimator.
Adam Lee, Rickard Sandberg, Genaro Sucarrat   +2 more
wiley   +1 more source

Sequential Outlier Detection in Nonstationary Time Series

Journal 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, Patrick Bastian, Holger Dette   +2 more
wiley   +1 more source

Stability of fractional positive nonlinear systems

Archives of Control Sciences, 2015
The conditions for positivity and stability of a class of fractional nonlinear continuous-time systems are established. It is assumed that the nonlinear vector function is continuous, satisfies the Lipschitz condition and the linear part is described by ...
Kaczorek Tadeusz
doaj   +1 more source

Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley   +1 more source

Testing Distributional Granger Causality With Entropic Optimal Transport

Journal of Time Series Analysis, EarlyView.
ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley   +1 more source

Marchenko–Pastur Laws for Daniell Smoothed Periodograms

Journal of Time Series Analysis, EarlyView.
ABSTRACT Given a sample X0,…,Xn−1$$ {X}_0,\dots, {X}_{n-1} $$ from a d$$ d $$‐dimensional stationary time series (Xt)t∈ℤ$$ {\left({X}_t\right)}_{t\in \mathbb{Z}} $$, the most commonly used estimator for the spectral density matrix F(θ)$$ F\left(\theta \right) $$ at a given frequency θ∈[0,2π)$$ \theta \in \left[0,2\pi \right) $$ is the Daniell smoothed ...
Ben Deitmar
wiley   +1 more source

Reinforcement Learning for Jump‐Diffusions, With Financial Applications

Mathematical Finance, EarlyView.
ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley   +1 more source