INTRODUCTION Statistical models for assessing risk of type 2 diabetes are usually additive with linear terms that use non-nationally representative data. The objective of this study was to use nationally representative data on diabetes risk factors and spline regression models to determine the ability of models with nonlinear and interaction terms to assess the risk of type 2 diabetes. METHOD...

Multivariate adaptive regression splines (MARS) has been adopted as a popular surrogate function to model the unknown relationships between input and output variables in complex systems. Searching optimal solutions on complicated response surface of MARS serves important tasks various applications. In this paper, we present an efficient effective approach find global value models that incorpora...

Open-loop adaptive optics is a technique in which the turbulent wavefront is measured before it hits the deformable mirror for correction. We present a technique to model a deformable mirror working in open-loop based on multivariate adaptive regression splines (MARS), a non-parametric regression technique. The model's input is the wavefront correction to apply to the mirror and its output is t...

Inferred wind-related modifications of impact craters are observed in the vicinity of the Mars Pathfinder (MPF) site and in other regions of Mars. Mars Obiter Camera (MOC) images show three types of inferred wind-modified morphologies for craters 0.3–1 km in diameter. Such modifications could be related to seasonal variations of the strongest winds and a possible paleowind regime. Geomorphic ma...

In text-to-speech synthesis systems, the quality of the predicted prosody contours influences quality and naturalness of synthetic speech. This paper presents a new statistical model for prosody control that combines an ensemble learning technique using neural networks as base learners with feature relevance determination. This weighted neural network ensemble model was applied for both, phone ...

This work proposes a new method to classify multi-spectral satellite images based on multivariate adaptive regression splines (MARS) and compares this classification system with the more common parallelepiped and maximum likelihood (ML) methods. We apply the classification methods to the land cover classification of a test zone located in southwestern Spain. The basis of the MARS method and its...

Earthquake research has not yielded promising results because earthquakes have uncertain data parameters, and one of the methods to overcome problem parameters is nonparametric method, namely Multivariate Adaptive Regression Splines (MARS). Sumbawa Island part territory Indonesia in position three active earth plates, so prone earthquake hazards. Therefore, this important do. This study aimed a...

The aim of this research work is to build a regression model of air quality by using the multivariate adaptive regression splines (MARS) technique in the Oviedo urban area (northern Spain) at a local scale. To accomplish the objective of this study, the experimental data set made up of nitrogen oxides (NO x ), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3), and dust (PM10) was collected...

Dynamic programming is a multi-stage optimization method that is applicable to many problems in engineering. A statistical perspective of value function approximation in highdimensional, continuous-state stochastic dynamic programming (SDP) was first presented using orthogonal array (OA) experimental designs and multivariate adaptive regression splines (MARS). Given the popularity of artificial...