Studies the growth and proportion of different types of co-authored publications in theoretical population genetics. Explores the applicability of appropriate statistical model to the decline in the proportion of single-authored publication with time. Studies the applicability of selected statistical models to the distribution of authorship in publications of theoretical population genetics wit...

The expert package provides tools to create and manipulate empirical statistical models using expert opinion (or judgment). Here, the latter expression refers to a specific body of techniques to elicit the distribution of a random variable when data is scarce or unavailable. Opinions on the quantiles of the distribution are sought from experts in the field and aggregated into a final estimate. ...

A Hierarchical Statistical Model for Image Estimation Juan Liu December 16, 1998 Abstract In literature, we have seen many statistical models for images. We pay special attention to models for wavelet{domain image representations. Besides making iid assumptions about wavelet coe cients, there exist more sophisticate models exploring dependencies among wavelet coe cients. In this report, we prop...

Uncertainty plays an important role in analyzing and minimizing the errors in a given experimental data set in order to increase the reliability and quality of the obtained data. In this paper, we study biological data which is subject to technical limitations and errors, rendering the gathered data likely to be uncertain. By using fundamental numerical analysis approach, we have targeted to st...

High arsenic in natural groundwater in most of the tubewells of the PurbasthaliBlock II area of Burdwan district (W.B, India) has recently been focused as a serious environmental concern. This paper is intending to illustrate the statistical modeling of the arsenic contaminated groundwater to identify the interrelation of that arsenic contain with other participating groundwater parameters so t...

SECTION 1 explains why randomizations in the Le Cam sense have advantages over Markov kernels for the definition of the Le Cam distance between statistical models. SECTION 2 derives several facts about linear functionals, the most important being the existence of a linear map that projects onto the space of countably additive measures. SECTION 3 uses the projection map from Section 2, and compa...

Hypothesis testing in distributed source models for the electro- or magnetoencephalogram is generally performed for each voxel separately. Derived from the analysis of functional magnetic resonance imaging data, such a statistical parametric map (SPM) ignores the spatial smoothing in hypothesis testing with distributed source models. For example, when intending to test a single voxel, actually ...

We analyze phenomenologically several models for the high-energy scattering of hadrons through fixed, large angles. The emphasis is on trying to isolate and understand those aspects of hadronic forces which are important at large angles. We review the fixed-angle-lower bounds derived from analyticity and discuss how simple geometrical concepts can be used to guide our extrapolation of cross sec...

An increasing amount of data can be recorded automatically during surgeries. This has led to a recent interest in methods that allow statistical modeling of surgical workflow from this data. One main challenge of these methods is how to automatically generate a statistical model from a set of recorded surgeries. In this paper we will review different methods and show advantages and drawbacks.

BACKGROUND Primary studies examining the accuracy of a continuous test evaluate its sensitivity and specificity at one or more thresholds. Meta-analysts then usually perform a separate meta-analysis for each threshold. However, the number of studies available for each threshold is often very different, as primary studies are inconsistent in the thresholds reported. Furthermore, of concern is se...