Results 121 to 130 of about 7,656,330 (292)

Infinitesimal Lipschitz Equisingularity: Genericity and Necessity

, 2019
In earlier work we used the double of an ideal to define in integral closure terms a notion of infinitesimal Lipschitz equisingularity for hypersurfaces. We describe different ways of extending this notion to general spaces, and show the most restrictive
Gaffney, Terence
core   +1 more source

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

Journal 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

Dilatation, Pointwise Lipschitz Constants, and Condition N on Curves

Michigan Mathematical Journal, 2014
A quasiconformal mapping between domains in the Euclidean \(n\)-space is absolutely continuous on almost every curve with respect to the \(n\)-modulus and hence satisfies the Lusin condition, i.e., it maps sets of zero \(1\)-measure to sets of zero \(1\)-measure, on such curves.
openaire   +3 more sources

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

Copie-Buch von Geh.-Rath. Professor Dr. phil. R. Lipschitz Bonn. No. 1 / Brief an Herr College [Leopold Kronecker]!

, 1885
Adressat mutmaßlich ermittelt durch Inhalt des Briefes von Rudolf Lipschitz an Hermann Bonitz vom 23.12.1884.R.
Lipschitz, Rudolf
core  

Letter Written by George Lipschitz to the Bryant College Service Club Dated December 29, 1942 [PDF]

, 1942
[Transcription begins] 54th Medical Battalion Camp Edwards, Mass. December 29, 1942. Dear Friends, Thanks so much for the Christmas gift. Honestly, it did help to make my holiday complete. The package arrived in good condition on Christmas Day.
Lipschitz, George
core  

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

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