How to estimate statistical characteristics based on a sample: Nonparametric maximum likelihood approach leads to sample mean, sample variance, etc.

© Springer International Publishing AG 2018. In many practical situations, we need to estimate different statistical characteristics based on a sample. In some cases, we know that the corresponding probability distribution belongs to a known finite-parametric family of distributions. In such cases,...

Full description

Saved in:

Bibliographic Details
Main Authors:	Vladik Kreinovich, Thongchai Dumrongpokaphan
Format:	Book Series
Published:	2018
Subjects:	Computer Science
Online Access:	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037861764&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/58566
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Chiang Mai University

id	th-cmuir.6653943832-58566
record_format	dspace
spelling	th-cmuir.6653943832-585662018-09-05T04:26:20Z How to estimate statistical characteristics based on a sample: Nonparametric maximum likelihood approach leads to sample mean, sample variance, etc. Vladik Kreinovich Thongchai Dumrongpokaphan Computer Science © Springer International Publishing AG 2018. In many practical situations, we need to estimate different statistical characteristics based on a sample. In some cases, we know that the corresponding probability distribution belongs to a known finite-parametric family of distributions. In such cases, a reasonable idea is to use the Maximum Likelihood method to estimate the corresponding parameters, and then to compute the value of the desired statistical characteristic for the distribution with these parameters. In some practical situations, we do not know any family containing the unknown distribution. We show that in such nonparametric cases, the Maximum Likelihood approach leads to the use of sample mean, sample variance, etc. 2018-09-05T04:26:20Z 2018-09-05T04:26:20Z 2018-01-01 Book Series 1860949X 2-s2.0-85037861764 10.1007/978-3-319-70942-0_11 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037861764&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/58566
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
topic	Computer Science
spellingShingle	Computer Science Vladik Kreinovich Thongchai Dumrongpokaphan How to estimate statistical characteristics based on a sample: Nonparametric maximum likelihood approach leads to sample mean, sample variance, etc.
description	© Springer International Publishing AG 2018. In many practical situations, we need to estimate different statistical characteristics based on a sample. In some cases, we know that the corresponding probability distribution belongs to a known finite-parametric family of distributions. In such cases, a reasonable idea is to use the Maximum Likelihood method to estimate the corresponding parameters, and then to compute the value of the desired statistical characteristic for the distribution with these parameters. In some practical situations, we do not know any family containing the unknown distribution. We show that in such nonparametric cases, the Maximum Likelihood approach leads to the use of sample mean, sample variance, etc.
format	Book Series
author	Vladik Kreinovich Thongchai Dumrongpokaphan
author_facet	Vladik Kreinovich Thongchai Dumrongpokaphan
author_sort	Vladik Kreinovich
title	How to estimate statistical characteristics based on a sample: Nonparametric maximum likelihood approach leads to sample mean, sample variance, etc.
title_short	How to estimate statistical characteristics based on a sample: Nonparametric maximum likelihood approach leads to sample mean, sample variance, etc.
title_full	How to estimate statistical characteristics based on a sample: Nonparametric maximum likelihood approach leads to sample mean, sample variance, etc.
title_fullStr	How to estimate statistical characteristics based on a sample: Nonparametric maximum likelihood approach leads to sample mean, sample variance, etc.
title_full_unstemmed	How to estimate statistical characteristics based on a sample: Nonparametric maximum likelihood approach leads to sample mean, sample variance, etc.
title_sort	how to estimate statistical characteristics based on a sample: nonparametric maximum likelihood approach leads to sample mean, sample variance, etc.
publishDate	2018
url	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037861764&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/58566
_version_	1681425089383366656

How to estimate statistical characteristics based on a sample: Nonparametric maximum likelihood approach leads to sample mean, sample variance, etc.

Similar Items