Abstract Item-response models from the psychometric literature have been proposed for estimation of researcher capacity. Canonical items that can be incorporated in such to reflect performance are count data (e.g., number publications, citations). Count modeled by Rasch’s Poisson counts model assumes equidispersion (i.e., mean and variance must coincide). However, larger as compared underdisper...

We investigate some portfolio problems that consist of maximizing expected terminal wealth under the constraint of an upper bound for the risk, where we measure risk by the variance, but also by the Capital-at-Risk (CaR). The solution of the mean-variance problem has the same structure for any price process which follows an exponential Lévy process. The mean-CaR involves a quantile of the corre...

The choice of the optimal spherical radial basis function (SRBF) in local gravity field modelling from terrestrial gravity data is investigated. Various types of SRBFs are considered: the point-mass kernel, radial multipoles, Poisson wavelets, and the Poisson kernel. The analytical expressions for the Poisson kernel, the point-mass kernel and the radial multipoles are well known, while for the ...

Abstract This work introduces and compares approaches for estimating rare-event probabilities related to the number of edges in random geometric graph on a Poisson point process. In one-dimensional setting, we derive closed-form expressions variety conditional develop Monte Carlo algorithms this basis. We prove rigorously reduction variance when compared crude estimators illustrate magnitude im...

The repeated presentation of an identical visual stimulus in the receptive field of a neuron may evoke different spiking patterns at each trial. Probabilistic methods are essential to understand the functional role of this variance within the neural activity. In that case, a Poisson process is the most common model of trial-to-trial variability. For a Poisson process, the variance of the spike ...

25 The repeated presentation of an identical visual stimulus in the receptive field of a neuron may evoke 26 different spiking patterns at each trial. Probabilistic methods are essential to understand the functional 27 role of this variance within the neural activity. In that case, a Poisson process is the most common model 28 of trial-to-trial variability. For a Poisson process, the variance o...

OBJECTIVE To empirically compare the Cox, log-binomial, Poisson and logistic regressions to obtain estimates of prevalence ratios (PR) in cross-sectional studies. METHODS Data from a population-based cross-sectional epidemiological study (n = 2072) on elderly people in Sao Paulo (Southeastern Brazil), conducted between May 2003 and April 2005, were used. Diagnoses of dementia, possible cases ...

We present a fast algorithm for image restoration in the presence of Poisson noise. Our approach is based on (1) the minimization of an unbiased estimate of the MSE for Poisson noise, (2) a linear parametrization of the denoising process and (3) the preservation of Poisson statistics across scales within the Haar DWT. The minimization of the MSE estimate is performed independently in each wavel...

Let us begin by recalling the definition of two familiar processes, a Brownian motion and a Poisson process. A real-valued process B = {B t : t ≥ 0} defined on a probability space (Ω, F , P) is said to be a Brownian motion if the following hold: (i) The paths of B are P-almost surely continuous. (ii) P(B 0 = 0) = 1. (iii) For 0 ≤ s ≤ t, B t − B s is equal in distribution to B t−s. (iv) For 0 ≤ ...