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.
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
Copyright Date
2005
Language
en
File Format
application/pdf
Recommended Citation
Vardeman, Stephen B. and Lee, Chiang-Sheng, "Likelihood-based statistical estimation from quantized data" (2005). Industrial and Manufacturing Systems Engineering Publications. 142.
https://lib.dr.iastate.edu/imse_pubs/142
Included in
Industrial Engineering Commons, Statistics and Probability Commons, Systems Engineering Commons
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.