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Nonlinear systems of affine control inputs overarch many sensor fusion instances. Analyzing whether a state variable in such a nonlinear system can be estimated (i.e., observability) informs better estimator design. Among the research on…

Systems and Control · Electrical Eng. & Systems 2022-07-19 Jianzhu Huai , Yukai Lin , Yujia Zhang

The goal of this paper is to provide some tools for nonparametric estimation and inference in psychological and economic experiments. We consider an experimental framework in which each of $n$subjects provides $T$ responses to a vector of…

Econometrics · Economics 2019-12-10 Raffaello Seri , Samuele Centorrino , Michele Bernasconi

On the basis of the author's earlier results, a new source function for a numerical wind-wave model optimized by the criterion of accuracy and speed of calculation is substantiated. The proposed source function includes (a) an optimized…

Atmospheric and Oceanic Physics · Physics 2010-06-30 Vladislav Polnikov

In this work, we propose a new detector function based on wavelet transform to discriminate between turbulent and non-turbulent regions in an intermittent velocity signal. The derivative-based detector function, which is commonly used in…

Fluid Dynamics · Physics 2023-01-02 Satyajit De , Aditya Anand , Sourabh S. Diwan

We introduce the Weak-form Estimation of Nonlinear Dynamics (WENDy) method for estimating model parameters for non-linear systems of ODEs. Without relying on any numerical differential equation solvers, WENDy computes accurate estimates and…

Machine Learning · Computer Science 2023-11-27 David M. Bortz , Daniel A. Messenger , Vanja Dukic

Wavelet based algorithms in numerical analysis are similar to other transform methods in that vectors and operators are expanded into a basis and the computations take place in this new system of coordinates. However, due to the recursive…

comp-gas · Physics 2008-02-03 G. Beylkin

In recent years, a new method for experimental nonlinear modal analysis has been developed, which is based on the extended periodic motion concept. The method is well suited to experimentally obtain amplitude-dependent modal properties…

Systems and Control · Electrical Eng. & Systems 2021-08-16 Maren Scheel

In this paper, we propose a Network-Weighted Functional Regression (NWFR) model, an extension of Spatially Weighted Functional Regression (SWFR) to functional data defined on network-structured settings. To asses predictive uncertainity, we…

Methodology · Statistics 2025-06-02 Elvira Romano , Antonio Irpino , Claire Miller

We propose a novel method for testing the null hypothesis of no effect of a covariate on the response in the context of functional linear concurrent regression. We establish an equivalent random effects formulation of our functional…

Methodology · Statistics 2019-12-16 Rahul Ghosal , Arnab Maity

Parameter estimation in linear errors-in-variables models typically requires that the measurement error distribution be known (or estimable from replicate data). A generalized method of moments approach can be used to estimate model…

Methodology · Statistics 2018-12-04 Linh Nghiem , Michael Byrd , Cornelis Potgieter

In this work we build optimal experimental designs for precise estimation of the functional coefficient of a function-on-function linear regression model where both the response and the factors are continuous functions of time. After…

Methodology · Statistics 2024-12-20 Caterina May , Theodoros Ladas , Davide Pigoli , Kalliopi Mylona

In implementations of the functional data methods, the effect of the initial choice of an orthonormal basis has not gained much attention in the past. Typically, several standard bases such as Fourier, wavelets, splines, etc. are considered…

Machine Learning · Statistics 2021-03-15 Rani Basna , Hiba Nassar , Krzysztof Podgórski

This paper is concerned with modeling the dependence structure of two (or more) time-series in the presence of a (possible multivariate) covariate which may include past values of the time series. We assume that the covariate influences…

Statistics Theory · Mathematics 2018-12-11 Natalie Neumeyer , Marek Omelka , Sarka Hudecova

This paper provides a general framework for testing instrument validity in heterogeneous causal effect models. The generalization includes the cases where the treatment can be multivalued ordered or unordered. Based on a series of testable…

Econometrics · Economics 2023-10-11 Zhenting Sun

We propose generalized additive partial linear models for complex data which allow one to capture nonlinear patterns of some covariates, in the presence of linear components. The proposed method improves estimation efficiency and increases…

Statistics Theory · Mathematics 2014-05-26 Li Wang , Lan Xue , Annie Qu , Hua Liang

In the present paper, we derive lower bounds for the risk of the nonparametric empirical Bayes estimators. In order to attain the optimal convergence rate, we propose generalization of the linear empirical Bayes estimation method which…

Statistics Theory · Mathematics 2013-06-12 Rida Benhaddou , Marianna Pensky

In this paper, we introduce a wavelet-based method for estimating the EDR space in Li's semiparametric regression model for achieving dimension reduction. This method is obtained by using linear wavelet estimators of the density and…

Statistics Theory · Mathematics 2020-05-04 Emmanuel de Dieu Nkou , Guy Martial Nkiet

A novel approach for modeling the progress variable reaction rate in Large Eddy Simulations of turbulent and reacting flows is proposed. This is done in the context of two popular flamelet models which require the progress variable variance…

Fluid Dynamics · Physics 2018-10-18 Zacharias Nikolaou , Luc Vervisch

In this paper we present the applications of methods from wavelet analysis to polynomial approximations for a number of accelerator physics problems. In the general case we have the solution as a multiresolution expansion in the base of…

Accelerator Physics · Physics 2016-09-08 Antonina N. Fedorova , Michael G. Zeitlin

In this paper we propose a solution to the problem of parameter estimation of nonlinearly parameterized regressions--continuous or discrete time--and apply it for system identification and adaptive control. We restrict our attention to…

Optimization and Control · Mathematics 2019-10-18 Romeo Ortega , Vladislav Gromov , Emmanuel Nuño , Anton Pyrkin , Jose Guadalupe Romero