EMPIRICAL BAYES ANALYSIS OF TWO-FACTOR EXPERIMENTS UNDER INVERSE GAUSSIAN MODEL

نویسندگان: ثبت نشده
چکیده مقاله:

A two-factor experiment with interaction between factors wherein observations follow an Inverse Gaussian model is considered. Analysis of the experiment is approached via an empirical Bayes procedure. The conjugate family of prior distributions is considered. Bayes and empirical Bayes estimators are derived. Application of the procedure is illustrated on a data set, which has previously been analyzed by other authors.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

empirical bayes analysis of two-factor experiments under inverse gaussian model

a two-factor experiment with interaction between factors wherein observations follow an inverse gaussian model is considered. analysis of the experiment is approached via an empirical bayes procedure. the conjugate family of prior distributions is considered. bayes and empirical bayes estimators are derived. application of the procedure is illustrated on a data set, which has previously been an...

متن کامل

Limiting Properties of Empirical Bayes Estimators in a Two-Factor Experiment under Inverse Gaussian Model

The empirical Bayes estimators of treatment effects in a factorial experiment were derived and their asymptotic properties were explored. It was shown that they were asymptotically optimal and the estimator of the scale parameter had a limiting gamma distribution while the estimators of the factor effects had a limiting multivariate normal distribution. A Bootstrap analysis was performed to ill...

متن کامل

limiting properties of empirical bayes estimators in a two-factor experiment under inverse gaussian model

the empirical bayes estimators of treatment effects in a factorial experiment were derived and their asymptotic properties were explored. it was shown that they were asymptotically optimal and the estimator of the scale parameter had a limiting gamma distribution while the estimators of the factor effects had a limiting multivariate normal distribution. a bootstrap analysis was performed to ill...

متن کامل

Regression Analysis under Inverse Gaussian Model: Repeated Observation Case

 Traditional regression analyses assume normality of observations and independence of mean and variance. However, there are many examples in science and Technology where the observations come from a skewed distribution and moreover there is a functional dependence between variance and mean. In this article, we propose a method for regression analysis under Inverse Gaussian model when th...

متن کامل

THE EMPIRICAL BAYES METHOD OF ANALYSIS OF A SERIES OF EXPERIMENTS

The classical method of analysis of a series of experiments is somewhat involved in being conditional on various, occasionally unrealistic, assumptions such as homogeneity of variances of experimental error, lack of interactions of treatments and places,etc. In this work, we adopt a Bayesian view to account for such heterogeneities. Our appoach is illustrated by a real series of experiment...

متن کامل

Empirical Bayes Analysis of Quantitative Proteomics Experiments

BACKGROUND Advances in mass spectrometry-based proteomics have enabled the incorporation of proteomic data into systems approaches to biology. However, development of analytical methods has lagged behind. Here we describe an empirical Bayes framework for quantitative proteomics data analysis. The method provides a statistical description of each experiment, including the number of proteins that...

متن کامل

منابع من

با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ذخیره در منابع من قبلا به منابع من ذحیره شده

{@ msg_add @}


عنوان ژورنال

دوره 14  شماره 1

صفحات  -

تاریخ انتشار 2003-03-01

با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.

کلمات کلیدی

میزبانی شده توسط پلتفرم ابری doprax.com

copyright © 2015-2023