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

Improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies

BACKGROUND: Ion Torrent and Ion Proton are semiconductor-based sequencing technologies that feature rapid sequencing speed and low upfront and operating costs, thanks to the avoidance of modified nucleotides and optical measurements. Despite of these advantages, however, Ion semiconductor sequencing technologies suffer much reduced sequencing accuracy at the genomic loci with homopolymer repeats of the same nucleotide. Such limitation significantly reduces its efficiency for the biological applications aiming at accurately identifying various genetic variants. RESULTS: In this study, we propose a Bayesian inference-based method that takes the advantage of the signal distributions of the electrical voltages that are measured for all the homopolymers of a fixed length. By cross-referencing the length of homopolymers in the reference genome and the voltage signal distribution derived from the experiment, the proposed integrated model significantly improves the alignment accuracy around the homopolymer regions. CONCLUSIONS: Besides improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies with the proposed model, similar strategies can also be used on other high-throughput sequencing technologies that share similar limitations

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

Minimum distance measurement errors model fitting

Thesis (Ph. D.)--Michigan State University. Department of Statistics and Probability, 2006Includes bibliographical references (pages 93-95