Results 61 to 70 of about 424,647 (298)
Parameter estimation of ODE's via nonparametric estimators [PDF]
, 2007 Ordinary differential equations (ODE's) are widespread models in physics, chemistry and biology. In particular, this mathematical formalism is used for describing the evolution of complex systems and it might consist of high-dimensional sets of coupled ...
Brunel, Nicolas J-B.
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Detection of nonlinearity, discontinuity and interactions in generalized regression models
Statistical ModellingIn generalized regression models, the effect of continuous covariates is commonly assumed to be linear. This assumption, however, may be too restrictive in applications and may lead to biased effect estimates and decreased predictive ability. While a multitude of alternatives for the flexible modelling of continuous covariates have been proposed ...
Spuck, Nikolai +2 more
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Estimation of nonlinear models with Berkson measurement errors
, 2005 This paper is concerned with general nonlinear regression models where the predictor variables are subject to Berkson-type measurement errors. The measurement errors are assumed to have a general parametric distribution, which is not necessarily normal ...
Wang, Liqun
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A specification test for nonlinear nonstationary models [PDF]
, 2012 We provide a limit theory for a general class of kernel smoothed U-statistics that may be used for specification testing in time series regression with nonstationary data.
Phillips, Peter C. B., Wang, Qiying
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Advanced Engineering Materials, EarlyView.Laser surface texturing significantly improves the corrosion resistance and mechanical strength of 3D‐printed iron polylactic acid (Ir‐PLA) for marine applications. Optimal laser parameters reduce corrosion by 80% and enhance tensile strength by 25% and ductility by 15%.
Mohammad Rezayat +6 more
wiley +1 more source
Marginal integration for nonparametric causal inference
, 2015 We consider the problem of inferring the total causal effect of a single variable intervention on a (response) variable of interest. We propose a certain marginal integration regression technique for a very general class of potentially nonlinear ...
Bühlmann, Peter, Ernest, Jan
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Probabilistic Nonlinear Soft Sensor Modeling Based on Generative Topographic Mapping Regression
IEEE Access, 2018 Projection regression is an important tool for process soft sensing in order to eliminate redundant information and obtain proper data features. As most industrial process is intrinsically nonlinear and process variables are collected in random noise environment, it is significant to adopt probabilistic nonlinear latent variable model to carry out ...
Xiaofeng Yuan, Zhiwen Chen, Yalin Wang
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On one algorithm of generating nonlinear regression models and its computer realization
E3S Web of Conferences, 2023 The tasks of statistical processing of experimental data arise in different areas of human activity. In this regard, the development of algorithms and corresponding computer programs that allow such processing and satisfy certain conditions is an important task.
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Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.In this experimental study, the mechanical properties of additively manufactured Ti‐6Al‐4V lattice structures of different geometries are characterized using compression, four point bending and fatigue testing. While TPMS designs show superior fatigue resistance, SplitP and Honeycomb lattice structures combine high stiffness and strength. The resulting
Klaus Burkart +3 more
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