Incidence and Location of Eastern Pineshoot Borer Damage in Some Scotch Pine Christmas Tree Plantations in Michigan (Lepidoptera: Olethreutidae)

A survey of Christmas tree farms in Michigan revealed that 26% of the Scotch pine Christmas trees have one or more shoots injured by the eastern pineshoot borer, Eucosma gloriola Heinrich. Most attacks occurred on lateral branches in the top half of the tree. Only 2% of the observed trees had pineshoot borer injury on the terminal leader. Control except for normal shearing, was not recommended for most plantations

Confidence sets for split points in decision trees

We investigate the problem of finding confidence sets for split points in decision trees (CART). Our main results establish the asymptotic distribution of the least squares estimators and some associated residual sum of squares statistics in a binary decision tree approximation to a smooth regression curve. Cube-root asymptotics with nonnormal limit distributions are involved. We study various confidence sets for the split point, one calibrated using the subsampling bootstrap, and others calibrated using plug-in estimates of some nuisance parameters. The performance of the confidence sets is assessed in a simulation study. A motivation for developing such confidence sets comes from the problem of phosphorus pollution in the Everglades. Ecologists have suggested that split points provide a phosphorus threshold at which biological imbalance occurs, and the lower endpoint of the confidence set may be interpreted as a level that is protective of the ecosystem. This is illustrated using data from a Duke University Wetlands Center phosphorus dosing study in the Everglades.Comment: Published at http://dx.doi.org/10.1214/009053606000001415 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Empirical Likelihood based on Hypothesis Testing

AMS classifications: 62G10; 62G20; 62G30;estimation;testing;likelihood

Visualizing Multiple Quantile Plots

Multiple quantile plots provide a powerful graphical method for comparing the distributions of two or more populations. This paper develops a method of visualizing triple quantile plots and their associated confidence tubes, thus extending the notion of a QQ plot to three dimensions. More specifically, we consider three independent one-dimensional random samples with corresponding quantile functions Q1, Q2 and Q3, respectively. The triple quantile (QQQ) plot is then defined as the three-dimensional curve Q(p) = (Q1(p);Q2(p);Q3(p)); where 0Confidence region;empirical likelihood;quantile plot;three-sample com- parison

Proportional hazards models with continuous marks

For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates [Prentice et al. Biometrics 34 (1978) 541--554]. This article studies an extension of this approach to allow a continuum of competing risks, in which the cause of failure is replaced by a continuous mark only observed at the failure time. We develop inference for the proportional hazards model in which the regression parameters depend nonparametrically on the mark and the baseline hazard depends nonparametrically on both time and mark. This work is motivated by the need to assess HIV vaccine efficacy, while taking into account the genetic divergence of infecting HIV viruses in trial participants from the HIV strain that is contained in the vaccine, and adjusting for covariate effects. Mark-specific vaccine efficacy is expressed in terms of one of the regression functions in the mark-specific proportional hazards model. The new approach is evaluated in simulations and applied to the first HIV vaccine efficacy trial.Comment: Published in at http://dx.doi.org/10.1214/07-AOS554 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org