Exploring spatial nonlinearity using additive approximation

Exploring spatial nonlinearity using additive approximation

ZUDI LU, ARVID LUNDERVOLD, DAG TJøSTHEIM and QIWEI YAO Department of Statistics, London School of Economics, London WC2A 2AE, UK Institute of Systems Science, Academy of Mathematics and Systems Sciences Chinese Academy of Sciences, Beijing 100080, China Department of Physiology, University of Bergen, 5007 Bergen, Norway Department of Mathematics, University of Bergen, 5007 Bergen, Norway. E-mai...

Spatial and Temporal Rainfall Approximation Using Additive Models

Approximation of an additive mapping in various normed spaces

In this paper, using the fixed point and direct methods, we prove the generalized Hyers-Ulam-Rassias stability of the following Cauchy-Jensen additive functional equation: begin{equation}label{main} fleft(frac{x+y+z}{2}right)+fleft(frac{x-y+z}{2}right)=f(x)+f(z)end{equation} in various normed spaces. The concept of Hyers-Ulam-Rassias stability originated from Th. M. Rassias’ stability theorem t...

Fast Algorithm for Sparse Signal Approximation using Multiple Additive Dictionaries

There are several models for sparse approximation: one where a signal is a sparse linear combination of vectors over a redundant dictionary and a second model in which a collection of signals is a simultaneous sparse linear combination over a single dictionary. In this work, interpolate between these two models to synthesize a single signal of interest from K highly incoherent dictionaries whil...

Exploring nonlinearity with random field regression

Random field regression models provide an extremely flexible way to investigate nonlinearity in economic data. This paper introduces a new approach to interpreting such models, which may allow for improved inference about the possible parametric specification of nonlinearity. This paper is forthcoming in Applied Economics Letters. Corresponding author. Email: [email protected]. The views ex...