Campus Units

Industrial and Manufacturing Systems Engineering, Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2005

Journal or Book Title

IEEE Transactions on Instrumentation and Measurement

Volume

54

Issue

1

First Page

409

Last Page

414

DOI

10.1109/TIM.2004.838912

Abstract

Most standard statistical methods treat numerical data as if they were real (infinite-number-of-decimal-places) observations. The issue of quantization or digital resolution can render such methods inappropriate and misleading. This article discusses some of the difficulties of interpretation and corresponding difficulties of inference arising in even very simple measurement contexts, once the presence of quantization is admitted. It then argues (using the simple case of confidence interval estimation based on a quantized random sample from a normal distribution as a vehicle) for the use of statistical methods based on "rounded data likelihood functions" as an effective way of handling the matter.

Comments

This is a manuscript of an article published as Likelihood-based statistical estimation from quantized data. IEEE Transactions on Instrumentation and Measurement, 2005, Vol. 54, No. 1, pp. 409-414. With Chiang-Sheng Lee. Posted with permission.

Rights

© 2005 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Copyright Owner

IEEE

Language

en

File Format

application/pdf

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