We propose a simple stochastic model for an author’s production/citation process in order to investigate the recently proposed hindex for measuring an author’s research output and its impact. The parametric model distinguishes between an author’s publication process and the subsequent citation processes of the published papers. This allows us to investigate different scenarios such as varying t...

This paper deals with the identification of treatment effects when the outcome variable is ordered. If outcomes are measured ordinally, previously developed methods to investigate the impact of an endogenous binary regressor on average outcomes cannot be applied as the expectation of an ordered variable, in its strict sense, does not exist, and a shift in focus to distributional effects is indi...

Sharp non-parametric bounds on the winner’s curse effects (the difference between the mean value and the mean value conditional on winning) are derived for sealed-bid auctions with affiliated values. Both firstand second-price formats are considered. In addition, sharp bounds are derived on the competitive effect, the difference between the mean value conditional on winning and the mean bid. Al...

The identification of human basic actions plays an important role for recognizing human activities in complex scene. In this paper we propose an approach for automatic human action recognition. The parametric model of human is extracted from image sequences using motion/texture based human detection and tracking. Action features from its model are carefully defined into the action interaction r...

due to its critical impact and significant destructive nature during and after seismic events, soil liquefaction and liquefactioninduced lateral ground spreading have been increasingly important topics in the geotechnical earthquake engineering field during the past four decades. the aim of this research is to develop an empirical model for the assessment of liquefaction-induced lateral ground ...

We propose a series-based nonparametric specification test for regression function when data are spatially dependent, the “space” being of general economic or social nature. Dependence can be parametric, parametric with increasing dimension, semiparametric any combination thereof, thus covering vast variety settings. These include spatial error models varying types and levels complexity. Under ...

Abstract Graph pooling methods provide mechanisms for structure reduction that are intended to ease the diffusion of context between nodes further in graph, and typically leverage community discovery or node edge pruning heuristics. In this paper, we introduce a novel technique which borrows from classical results graph theory is non-parametric generalizes well graphs different nature connectiv...

Diffusion MRI is a noninvasive imaging modality that allows for the estimation and visualization of white matter connectivity patterns in the human brain. However, due to the low signal-to-noise ratio (SNR) nature of diffusion data, deriving useful statistics from the data is adversely affected by different sources of measurement noise. This is aggravated by the fact that the sampling distribut...

The Basso, Beattie, Bresnahan (BBB) open field locomotor scale is a popular measure of functional recovery following spinal cord injury (SCI). To examine the metric properties of the scale, we performed detailed analyses of BBB scores from 643 rats with moderate and severe SCI (12.5, 25, or 50 mm MASCIS) from two different laboratories. The analyses revealed that the BBB scale is ordinal in the...