We introduce the concept of a triad census of a digraph arid show how it can be used to enumerate various types of subgraph configurations. We give the basic probabilities needed for computing means and variances for a triad census under the U-MAN distribution for digraphs. These concepts are...

The authors review the literature on the delivery of ambulatory care to the urban poor by isolating the crucial variables affecting the supply and demand for such services and organizing the literature around these concepts. The state of health of the poor, perception of health, and cost of care...

The problem of drawing causal inferences from retrospective case-control studies is considered. A model for causal inference in prospective studies is reviewed and then applied to retrospective studies. The limitations of case-control studies are formulated in terms of the level of causally...

A description of a system of subroutines to compute solutions to the iteratively reweighted least squares problem is presented. The weights are determined from the data and linear fit and are computed as functions of the scaled residuals. Iteratively reweighted least squares is a part of robust...

This paper gives an alternative derivation of a Monte Carlo method that has been used to study robust estimators. Extensions of the technique to the regression case are also considered and some computational points are briefly mentioned.

We give some Monte Carlo results on the performance of two robust alternatives to least squares regression estimation - least absolute residuals and the one-step "sine" estimator. We show how to scale the residuals for the sine estimator to achieve constant efficiency at the Gaussian across...

This paper gives the formulas for and derivation of ridge regression methods when there are weights associated with each observation. A Bayesian motivation is used and various choices of k are discussed. A suggestion is made as to how to combine ridge regression with robust regression methods.

Bayesian estimation of the cell probabilities for the multinomial distribution (under a symmetric Dirichlet prior) leads to the use of a flattening constant [alpha] to smooth the raw cell proportions. The unsmoothed estimator corresponds to [alpha] = 0. The risk functions (under quadratic loss)...