1,345 research outputs found
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
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