Past research studies have documented the failure of the Insurance Regulatory Information System (IRIS) to provide adequate warning of insurer financial distress or insolvency. As a result, scholars have examined alternative parametric and nonparametric models to predict insurer insolvency. This study uses a neural network, a non-parametric alternative to past techniques, and shows how this met...

Reliability analysis is one of the significant applications of statistics. Many parametric and non-parametric techniques are available for reliability estimation based on precise life time observations, without considering the uncertainty of individual observations. But life time observations are not precise measurements but more or less fuzzy. Therefore by considering life time measurements as...

In 2003 and 2004, the ISO/IEC MPEG standardization committee added two amendments to their MPEG-4 audio coding standard. These amendments concern parametric coding techniques and encompass Spectral Band Replication (SBR), Sinusoidal Coding (SSC), and Parametric Stereo (PS). In this paper, we will give an overview of the basic ideas behind these techniques and references to more detailed informa...

This paper considered performance of content based image retrieval system using image representation nonparametric algorithms. Performance comparison of Epanechnikov, Gaussian and Histogram non-parametric algorithms was done in a generic image retrieval system. Chan & Vese and Cosine Angle Distance algorithms were used for segmentation and similarity matching respectively. The performance of th...

Data Envelopment Analysis (DEA) is a technique used to compare efficiency in various sectors such as hospitals, chain stores, and dealerships. It represents a set of linear programming techniques and uses deter-ministic data (inputs and outputs), in stable conditions. The DEA technique cannot be used when there is data with indeterministic nature, or when there is an environment with dynamic co...

The primary purpose of this chapter is to present an approach for developing nonparametric models for magneto-rheological (MR) dampers. Upon describing the approach adopted here, a non-parametric model for a commercial magneto-rheological damper is developed, and is compared with a parametric model from an earlier study. The results show that the proposed non-parametric model can more effective...

The talk gives a survey on some symbolic algorithmic methods for solving systems of algebraic equations with special emphasis on parametric systems. Besides complex solutions I consider also real solutions of systems including inequalities. The techniques described include the Euclidean algorithm, Grr obner bases, characteristic sets, univariate and multivariate Sturm-Sylvester theorems, compre...

Imputation is a widely used method for handling missing data. It consists in the replacement of missing values with plausible ones. Parametric and nonparametric techniques are generally adopted for modelling incomplete data. Both of them have advantages and drawbacks. Parametric techniques are parsimonious but depend on the model assumed, while nonparametric techniques are more flexible but req...

The paper presents a new unsupervised dimensionality reduction technique, called parametric t-SNE, that learns a parametric mapping between the high-dimensional data space and the low-dimensional latent space. Parametric t-SNE learns the parametric mapping in such a way that the local structure of the data is preserved as well as possible in the latent space. We evaluate the performance of para...

The aim of this study was to select one or several virus extraction techniques that enable simultaneous detection of enterovirus genomes and infectious particles in different types of urban sludge. Eight techniques were compared by using 16 different liquid and solid sludge samples. The numbers of infectious enteroviruses in cell cultures were determined by using the most-probable-number method...