Editor\u27s Preface and Table of Contents

These proceedings contain papers presented in the twenty-fourth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 29 - May 1, 2012

RELATIVE POTENCY ESTIMATION IN DIRECT BIOASSAY WITH MEASUREMENT ERRORS*

The dosage levels measured in direct bioassays are often contaminated with measurement errors, which are usually neglected in the statistical inference. This paper proposes several estimation procedures for the relative potencies in direct bioassays taking the measurement errors into account. Asymptotic theories are developed for constructing the confidence intervals. Numerical simulations are also included to compare different estimation procedures

Editor\u27s Preface and Table of Contents

These proceedings contain papers presented in the twenty-sixth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 27 - April 29, 2014

Editor\u27s Preface and Table of Contents

These proceedings contain papers presented in the twenty-second annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 25 - April 27, 2010

Preface

Prefac

Minimum distance regression model checking with Berkson measurement errors

Lack-of-fit testing of a regression model with Berkson measurement error has not been discussed in the literature to date. To fill this void, we propose a class of tests based on minimized integrated square distances between a nonparametric regression function estimator and the parametric model being fitted. We prove asymptotic normality of these test statistics under the null hypothesis and that of the corresponding minimum distance estimators under minimal conditions on the model being fitted. We also prove consistency of the proposed tests against a class of fixed alternatives and obtain their asymptotic power against a class of local alternatives orthogonal to the null hypothesis. These latter results are new even when there is no measurement error. A simulation that is included shows very desirable finite sample behavior of the proposed inference procedures.Comment: Published in at http://dx.doi.org/10.1214/07-AOS565 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Model checking in errors-in-variables regression

AbstractThis paper discusses a class of minimum distance tests for fitting a parametric regression model to a class of regression functions in the errors-in-variables model. These tests are based on certain minimized distances between a nonparametric regression function estimator and a deconvolution kernel estimator of the conditional expectation of the parametric model being fitted. The paper establishes the asymptotic normality of the proposed test statistics under the null hypothesis and that of the corresponding minimum distance estimators. We also prove the consistency of the proposed tests against a fixed alternative and obtain the asymptotic distributions for general local alternatives. Simulation studies show that the testing procedures are quite satisfactory in the preservation of the finite sample level and in terms of a power comparison

Quantum states with negative energy density in the Dirac field and quantum inequalities

Energy densities of the quantum states that are superposition of two multi-electron-positron states are examined. It is shown that the energy densities can be negative only when two multi-particle states have the same number of electrons and positrons or when one state has one more electron-positron pair than the other. In the cases in which negative energy could arise, we find that the energy is that of a positive constant plus a propagating part which oscillates between positive and negative, and the energy can dip to negative at some places at for a certain period of time if the quantum states are properly manipulated. It is demonstrated that the negative energy densities satisfy the quantum inequality. Our results also reveal that for a given particle content, the detection of negative energy is an operation that depends on the frame where any measurement is to be performed. This suggests that the sign of energy density for a quantum state may be a coordinate-dependent quantity in quantum theory.Comment: Revtex,9 pages, no figures, a couple of typos correcte