We propose a parametric class of phylogenetic diversity (PD) measures that are sensitive to both species abundance and species taxonomic or phylogenetic distances. This work extends the conventional parametric species-neutral approach (based on 'effective number of species' or Hill numbers) to take into account species relatedness, and also generalizes the traditional phylogenetic approach (bas...

The water maze is commonly used to assay spatial cognition, or, more generally, learning and memory in experimental rodent models. In the water maze, mice or rats are trained to navigate to a platform located below the water's surface. Spatial learning is then typically assessed in a probe test, where the platform is removed from the pool and the mouse or rat is allowed to search for it. Perfor...

Probability distributions of macaque complex cell responses to a large set of images were determined. Measures of selectivity were based on the overall shape of the response probability distribution, as quantified by either kurtosis or entropy. We call this non-parametric selectivity, in contrast to parametric selectivity, which measures tuning curve bandwidths. To examine how receptive field p...

In this paper, we compare several parametric and non-parametric models of diffusion in a unified framework that allows simultaneous model estimation and tractography. The framework uses the Unscented Kalman Filter (UKF) to compare several variants of spherical harmonics (SH), i.e., SH with sharpening, spherical deconvolution, SH with solid angle and also several parametric models like single an...

The main goal of the present study is testing asymmetric risk pricing and comparing it with pricing of traditional risk measures in Tehran Stock Market. Accordingly, a sample consisting of 101 companies listed in Tehran Stock Market during 2002-2013 went under investigation. In order to test asymmetric risk pricing, regression model of panel data was applied. The results revealed a positive and...

We explore risk preference elicitation when subjects choose directly from an exogenously specified set of lotteries. Our choice tasks differ incrementally, e.g., choosing between two lotteries to selecting a portfolio continuous bundled Arrow securities, and text spatial presentation. Each subject completes multiple instances five different tasks, responses for each task are summarized in param...

8 Efron (1979) introduced the bootstrap method for independent data but it can not be easily applied to spatial data because of their dependency. For spatial data that are correlated in terms of their locations in the underlying space the moving block bootstrap method is usually used to estimate the precision measures of the estimators. The precision of the moving block bootstrap estimators is ...

Time scale parametric spike train distances like the Victor and the van Rossum distances are often applied to study the neural code based on neural stimuli discrimination. Different neural coding hypotheses, such as rate or coincidence coding, can be assessed by combining a time scale parametric spike train distance with a classifier in order to obtain the optimal discrimination performance. Th...

OBJECTIVE Measurements from health-related quality-of-life (HRQoL) studies, although usually of an ordered categorical nature, are typically treated as continuous variables, allowing the calculation of mean values and the administration of parametric statistics, such as t-tests. We investigated whether parametric, compared to nonparametric, analyses of ordered categorical data may lead to diffe...

8 Efron (1979) introduced the bootstrap method for independent data but it can not be easily applied to spatial data because of their dependency. For spatial data that are correlated in terms of their locations in the underlying space the moving block bootstrap method is usually used to estimate the precision measures of the estimators. The precision of the moving block bootstrap estimators is ...