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In this work we propose a new kind of parameterized outer estimate of the united solution set to an interval parametric linear system. The new method has several advantages compared to the methods obtaining parameterized solutions…

Numerical Analysis · Mathematics 2020-04-02 Evgenija D. Popova

This paper proposes a new method, in the frequency domain, to define absorbing boundary conditions for general two-dimensional problems. The main feature of the method is that it can obtain boundary conditions from the discretized equations…

Classical Physics · Physics 2015-05-14 Denis Duhamel , Tien-Minh Nguyen

Methods of determination of constants of the Standard Model are considered. The constants values obtained now are presented and experiments for improving some values are pointed out. A few possible generalized models are considered together…

High Energy Physics - Phenomenology · Physics 2007-05-23 V. V. Khruschov

In this article, we propose a new method for calculating the mixed correlation coefficient (Pearson, polyserial and polychoric) matrix and its covariance matrix based on the GMM framework. We build moment equations for each coefficient and…

Computation · Statistics 2024-04-11 Ben Liu , Peng Zhang , Yi Feng , Xiaowei Lou

The Median Based Unit Weibull is a new 2 parameter unit Weibull distribution defined on the unit interval (0,1). Estimation of the parameters using MLE encountered some problems like large variance. Using generalized method of moments…

Methodology · Statistics 2024-10-30 Iman Mohamed Attia

The paper proposes a formal estimation procedure for parameters of the fractional Poisson process (fPp). Such procedures are needed to make the fPp model usable in applied situations. The basic idea of fPp, motivated by experimental data…

Methodology · Statistics 2018-06-08 Dexter Cahoy , Vladimir V. Uchaikin , Wojbor A. Woyczynski

In the classic measurement error framework, covariates are contaminated by independent additive noise. This paper considers parameter estimation in such a linear errors-in-variables model where the unknown measurement error distribution is…

Methodology · Statistics 2023-10-24 Linh H. Nghiem , Cornelis J. Potgieter

Projection predictive inference is a decision theoretic Bayesian approach that decouples model estimation from decision making. Given a reference model previously built including all variables present in the data, projection predictive…

Methodology · Statistics 2020-10-15 Alejandro Catalina , Paul-Christian Bürkner , Aki Vehtari

This paper proposes a method to automatically construct or estimate Neyman-orthogonal moments in general models defined by a finite number of conditional moment restrictions (CMRs), with possibly different conditioning variables and…

Econometrics · Economics 2025-12-10 Facundo Argañaraz

The generalized problem of moments is a conic linear optimization problem over the convex cone of positive Borel measures with given support. It has a large variety of applications, including global optimization of polynomials and rational…

Optimization and Control · Mathematics 2018-11-14 Etienne de Klerk , Monique Laurent

Marginal model is a popular instrument for studying longitudinal data and cluster data. This paper investigates the estimator of marginal model with subgroup auxiliary information. To marginal model, we propose a new type of auxiliary…

Methodology · Statistics 2018-06-11 Jie He , Xiaogang Duan , Shumei Zhang , Hui Li

We describe various moment-based ensemble interpretation models for the construction of probabilistic temperature forecasts from ensembles. We apply the methods to one year of medium range ensemble forecasts and perform in and out of sample…

Atmospheric and Oceanic Physics · Physics 2007-05-23 Stephen Jewson

Advancement in manufacturing methods enable designing so called metamaterials with a tailor-made microstructure. Microstructure affects materials response within a length-scale, where we model this behavior by using the generalized…

Computational Engineering, Finance, and Science · Computer Science 2022-12-02 Bozo Vazic , Bilen Emek Abali , Pania Newell

This paper develops theory for feasible estimators of finite-dimensional parameters identified by general conditional quantile restrictions, under much weaker assumptions than previously seen in the literature. This includes instrumental…

Statistics Theory · Mathematics 2021-10-07 Luciano de Castro , Antonio F. Galvao , David M. Kaplan , Xin Liu

We provide a general and tractable framework under which all multiple yield curve modeling approaches based on affine processes, be it short rate, Libor market, or HJM modeling, can be consolidated. We model a numeraire process and…

Mathematical Finance · Quantitative Finance 2017-02-08 Christa Cuchiero , Claudio Fontana , Alessandro Gnoatto

This thesis is devoted to the study of affine processes and their applications in financial mathematics. In the first part we consider the theory of time-inhomogeneous affine processes on general state spaces. We present a concise setup for…

Pricing of Securities · Quantitative Finance 2015-12-11 Stefan Waldenberger

The Method of Moments [Pea94] is one of the most widely used methods in statistics for parameter estimation, by means of solving the system of equations that match the population and estimated moments. However, in practice and especially…

Statistics Theory · Mathematics 2019-04-16 Yihong Wu , Pengkun Yang

This paper is concerned with combined inference for point processes on the real line observed in a broken interval. For such processes, the classic history-based approach cannot be used. Instead, we adapt tools from sequential spatial point…

Methodology · Statistics 2015-06-04 M. N. M. van Lieshout

For the multivariate COGARCH process, we obtain explicit expressions for the second-order structure of the "squared returns" process observed on an equidistant grid. Based on this, we present a generalized method of moments estimator for…

Statistics Theory · Mathematics 2021-02-03 Thiago do Rêgo Sousa , Robert Stelzer

We propose a procedure for estimating the parameters of the Mittag-Leffler (ML) and the generalized Mittag-Leffler (GML) distributions. The algorithm is less restrictive, computationally simple, and necessary to make these models usable in…

Methodology · Statistics 2018-06-08 Dexter Cahoy