Disagreement Loop and Path Creation/Annihilation Algorithms for Binary Planar Markov Fields with Applications to Image Segmentation

Abstract. We introduce a class of Gibbs–Markov random fields built on regular tessellations that can be understood as discrete counterparts of Arak–Surgailis polygonal fields. We focus first on consistent polygonal fields, for which we show consistency, Markovianity and solvability by means of dynamic representations. Next, we develop disagreement loop as well as path creation and annihilation dynamics for their general Gibbsian modifications, which cover most lattice‐based Gibbs–Markov random fields subject to certain mild conditions. Applications to foreground–background image segmentation problems are discussed.     

Comparison of Regression Curves with Censored Responses

Abstract.  In this article, we introduce a procedure to test the equality of regression functions when the response variables are censored. The test is based on a comparison of Kaplan–Meier estimators of the distribution of the censored residuals. Kolmogorov–Smirnov- and Cramér–von Mises-type statistics are considered. Some asymptotic results are proved: weak convergence of the process of interest, convergence of the test statistics and behaviour of the process under local alternatives. We also describe a bootstrap procedure in order to approximate the critical values of the test. A simulation study and an application to a real data set conclude the paper.     

Love,necessity and opportunity: Changing patterns of marital age homogamy in the Netherlands, 1850–1993

Abstract. This article examines long-term trends in the pattern of age homogamy among first marriages, using vital registration data on all first marriages contracted between 1850 and 1993 in the Netherlands. After discussing the main mechanisms that could account for trends in age differences, we show that age differences between spouses narrowed considerably between 1850 and 1970. After 1970 the trend becomes less clear-cut.     

Dynamic Prediction by Landmarking in Event History Analysis

Abstract.  This article advocates the landmarking approach that dynamically adjusts predictive models for survival data during the follow up. This updating is achieved by directly fitting models for the individuals still at risk at the landmark point. Using this approach, simple proportional hazards models are able to catch the development over time for models with time-varying effects of covariates or data with time-dependent covariates (biomarkers). To smooth the effect of the landmarking, sequences of models are considered with parametric effects of the landmark time point and fitted by maximizing appropriate pseudo log-likelihoods that extend the partial log-likelihood to cover the landmarking approach.     

CENTRAL BANK SECRECY, INTEREST RATES, AND MONETARY CONTROL

We construct a dynamic rational expectations model of the federal funds and deposit market that provides a rationale for central bank secrecy about current monetary aggregate objectives. In this analysis, the Trading Desk values secrecy because it reduces the influence of monetary control policy on interest rates. We then examine actual U.S. experience with monetary control and determine that the reserve bias predicted by the model is present in the data from 1978 to 1985. Finally, we demonstrate that central bank secrecy may not lower the value of commercial banks.     

A Probabilistic Perspective on Re-Identifiability

A quasi-identifier is a set of attributes that can be used to re-identify entries in anonymized data sets. A group of individuals is considered about whom quasi-identifying numerical information is disclosed such as date of birth, age, weight, and height. The fraction of individuals is determined whose information is unique in that group and hence is identifiable unambiguously. Nonuniformity can be captured well by a single number, the Kullback-Leibler distance. For example sets of real microdata, given approximations based on Kullback-Leibler distances are accurate. Second, the effect of disclosing more specific or less specific information is analyzed experimentally. Third, the effect of correlation between numerical attributes is measured. A formula gives the re-identifiability level. The approximations are validated using publicly available demographic data sets.