Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in ris...

OBJECTIVE To adapt and develop a method for finding out what proportion of the variation among small areas in the number of births to married women is excess (systematic) variation over and above the chance (random) variation. METHODS We adopted a two-stage sampling procedure to select 20 sub-centres in south India. We contacted all households and collected information on recent births and so...

Most color image cameras today acquire only one out of the R, G, B values per pixel by means of a color filter array (CFA) in the hardware producing the so called ‘CFA image’. In-built software routines are required to undertake the task of obtaining the rest of the color information at each pixel through a process termed demosaicing. The most common CFA pattern is the well-known Bayer pattern ...

Modified Poisson regression, which combines a log Poisson regression model with robust variance estimation, is a useful alternative to log binomial regression for estimating relative risks. Previous studies have shown both analytically and by simulation that modified Poisson regression is appropriate for independent prospective data. This method is often applied to clustered prospective data, d...

Hall (2000) has described zero-inflated Poisson and binomial regression models that include random effects to account for excess zeros and additional sources of heterogeneity in the data. The authors of the present paper propose a general score test for the null hypothesis that variance components associated with these random effects are zero. For a zero-inflated Poisson model with random inter...

Motivated by non-Poisson stochastic variability found in service system arrival data, we extend established service system staffing algorithms using the square-root staffing formula to allow for non-Poisson arrival processes. We develop a general model of the non-Poisson nonstationary arrival process that includes as a special case the nonstationary Cox process (a modification of a Poisson proc...