Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.     

"Her" Marriage after the Revolutions

Recent social changes have made husbands' emotional investments and wives' perceptions of equity in the division of housework crucial for women's marital happiness. But wives are also happiest in their marriages when they share a strong normative commitment to lifelong marriage with their husbands and when their husbands take the lead in breadwinning. Thus our research suggests that elements of the new and the old promote marital happiness among contemporary wives.     

Scaling up CBOs for second‐order devolution in welfare reform

The Personal Responsibility and Work Opportunity Act of 1996 created a paradigm shift in the financing, organization, and delivery of welfare programs in the United States. The act shifted revenue and authority to states, giving them great discretion to determine the specifics of their programs. First‐order devolution, combined with time limits and work requirements, set in motion a chain of events that moved Temporary Assistance to Needy Families (TANF) recipients into the labor force and off state welfare rolls. Second‐order devolution shifted revenue and authority to community‐based organizations (CBOs) to help former recipients remain employed, advance to higher paying jobs, and move their families toward economic self‐sufficiency. Early findings from project innovations in Texas and other states raise doubts about the capacity of these organizations to achieve these goals. State funders will need to provide ongoing technical assistance and support to “scale up” the capacity of CBOs to plan, implement, and manage local innovations in welfare reform.     

Constrained allocation problems with single-peaked preferences: An axiomatic analysis

We introduce a new class of problems that contains two existing classes: allocation problems with single-peaked preferences and bankruptcy problems. On this class, we analyze the implications of well-known properties such as Pareto optimality, strategy-proofness, resource-monotonicity, no-envy, equal treatment of equals, and two new properties we introduce, hierarchical no-envy and independence of nonbinding constraints. Unlike earlier literature, we consider rules that allow free-disposability. We present characterizations of a rule we introduce on this domain. We relate this rule to well-known rules on the aforementioned subdomains. Based on this relation, we present a characterization of a well-known bankruptcy rule called the constrained equal awards rule. Received: 22 June 2000/Accepted: 21 March 2002 This paper is based on the first chapter of my Ph.D. thesis submitted to the University of Rochester. I wish to thank my advisor, William Thomson, for helpful comments and suggestions.     

Loss functions for estimation of extrema with an application to disease mapping

It is often of interest to find the maximum or near maxima among a set of vector‐valued parameters in a statistical model; in the case of disease mapping, for example, these correspond to relative‐risk “hotspots” where public‐health intervention may be needed. The general problem is one of estimating nonlinear functions of the ensemble of relative risks, but biased estimates result if posterior means are simply substituted into these nonlinear functions. The authors obtain better estimates of extrema from a new, weighted ranks squared error loss function. The derivation of these Bayes estimators assumes a hidden‐Markov random‐field model for relative risks, and their behaviour is illustrated with real and simulated data.     

An empirical examination of cost-adjusting in outpatient clinics

This paper presents an empirical methodology for examining cost-adjusting in relation to multiple-output health care providers. The methodology is subsequently implemented using a sample of California outpatient clinics. The empirical evidence is that these clinics do cost-adjust; that is, the clinics respond to low Medicare reimbursement by using lower quality to control the marginal costs of those patient groups not insured under a government-sponsored plan. In addition, clinics do not cost-adjust with respect to Medi-Cal patients, implying that various government reimbursement systems have different effects on a provider’s cost-adjusting behavior.