Results 21 to 30 of about 10,242 (124)
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
International Statistical Review, EarlyView.Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
State-of-the-Art in Sequential Change-Point Detection
, 2011 We provide an overview of the state-of-the-art in the area of sequential change-point detection assuming discrete time and known pre- and post-change distributions.
Polunchenko, Aleksey S. +1 more
core +1 more source
Financial Time Series Uncertainty: A Review of Probabilistic AI Applications
Journal of Economic Surveys, EarlyView.ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen +4 more
wiley +1 more source
Adaptive Estimation for Weakly Dependent Functional Times Series
Journal of Time Series Analysis, EarlyView.ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro +2 more
wiley +1 more source
, 2015 A sensitivity analysis in an observational study assesses the robustness of significant findings to unmeasured confounding. While sensitivity analyses in matched observational studies have been well addressed when there is a single outcome variable ...
Fogarty, Colin B., Small, Dylan S.
core +2 more sources
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
Worst-case estimation and asymptotic theory for models with unobservables [PDF]
, 2004 This paper proposes a worst-case approach for estimating econometric models containing unobservable variables. Worst-case estimators are robust against the adverse effects of unobservables.
Esteban-Bravo, Mercedes +1 more
core +1 more source
Testing the isotropy of high energy cosmic rays using spherical needlets
, 2013 For many decades, ultrahigh energy charged particles of unknown origin that can be observed from the ground have been a puzzle for particle physicists and astrophysicists.
Delabrouille, Jacques +3 more
core +4 more sources
Journal of Time Series Analysis, EarlyView.ABSTRACT We consider the problem of sequential (online) estimation of a single change point in a piecewise linear regression model under a Gaussian setup. We demonstrate that certain CUSUM‐type statistics attain the minimax optimal rates for localizing the change point.
Annika Hüselitz, Housen Li, Axel Munk
wiley +1 more source
General empirical Bayes wavelet methods and exactly adaptive minimax estimation
, 2005 In many statistical problems, stochastic signals can be represented as a sequence of noisy wavelet coefficients. In this paper, we develop general empirical Bayes methods for the estimation of true signal.
Zhang, Cun-Hui
core +2 more sources