This paper discusses trends and issues in selecting amplification for new, mainly nonlinear, types of hearing aids. Some-concerns are that nonvalidated prescription formulae may proliferate; that, through concentration on loudness normalization, alternative rationales are not being evaluated; and that most new fitting procedures for nonlinear hearing aids ignore the findings of research with li...

We describe extensions to the nonlinear modeling facilities in release 3 of S and Splus. These extensions provide classesand methods for fitting and analyzing nonlinear mixed effects models with the two-stage estimation method described by Lindstrom and Bates (1990). They are implemented in a combination of S and C code and complement the classes and methods for the linear mixed effects model t...

We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of rates of change and acceleration in latent growth curves-information available indirectly through traditional growth curve models when change patterns are nonlinear with respect to time. To illu...

The filtering problem, or dynamic data assimilation problem, is studied for linear and nonlinear systems with continuous state space and over discrete time steps. The paper presents filtering approaches based on the conjugate closed skew normal probability density. This distribution allows additional flexibility over the usual Gaussian approximations. With linear dynamic systems, the filtering ...

A detailed procedure to learn a nonlinear model together with its first-order derivative data is presented. Two correlated multilayer perceptron (MLP) neural networks providing the model and its first-order derivatives, respectively, are trained simultaneously. Applying this method to FET devices leads to nonlinear models for current and charge fitting derivative parameters. The training data i...

Among all the modeling approaches dedicated to cellular biology, differential algebra is particularly related to the well-established one based on nonlinear differential equations. In this paper, it is shown that differential algebra makes one of the model reduction methods both simple and algorithmic: the quasi-steady state approximation theory, in the particular setting of generalized chemica...

Abstract: A forward-backward (FB) unbiased finite impulse response (UFIR) smoothing algorithm is addressed to provide efficient denoising of piecewise-smooth signals with known or identifiable edge positions. Owing to the time-variant horizon, the algorithm unites advantages of linear structures with robustness of nonlinear ones. The FB UFIR smoother proposed has been examined in Gaussian and h...

In this paper we describe a new penalty-based model selection criterion for nonlinear models which is based on the influence of the noise in the fitting. According to Occam’s razor we should seek simpler models over complex ones and optimize the trade-off between model complexity and the accuracy of a model’s description to the training data. An empirical derivation is developed and computer si...

It is routine for audiologists to fit nonlinear hearing aids by using one of several current prescriptive formulae. While such an approach might result in acceptable fittings for single-channel analog compression hearing aids, its direct application to fitting current multichannel compression hearing aids may result in less than an optimal fit. In this paper, the effects of filter bandwidth, nu...

Exponential Smooth Transition Autoregressive (ESTAR) models can capture non-linear adjustment of the deviations from equilibrium conditions which may explain the economic behavior of many variables that appear non stationary from a linear viewpoint. Many researchers employ the Kapetanios test which has a unit root as the null and a stationary nonlinear model as the alternative. However this tes...