HOW TO ESTIMATE THE AMOUNT OF IMPORTANT CHARACTERISTICS MISSING IN A CONSUMERS SAMPLE BY USING BAYESIAN ESTIMATORS

Consumers surveys are conducted very often by many companies with the main objective of obtaining information about the opinions the consumers have about a specific prototype, product or service. In many situations the goal is to identify the characteristics that are considered important by the cons...

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Main Author: Mingoti Sueli A.
Format: Article
Language:English
Published: Sociedade Brasileira de Pesquisa Operacional 2001-01-01
Series:Pesquisa Operacional
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382001000100003
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spelling doaj-d7ef4ee62bc54513ab76ca900c6b11502020-11-24T22:49:08ZengSociedade Brasileira de Pesquisa OperacionalPesquisa Operacional0101-74381678-51422001-01-012113138HOW TO ESTIMATE THE AMOUNT OF IMPORTANT CHARACTERISTICS MISSING IN A CONSUMERS SAMPLE BY USING BAYESIAN ESTIMATORSMingoti Sueli A.Consumers surveys are conducted very often by many companies with the main objective of obtaining information about the opinions the consumers have about a specific prototype, product or service. In many situations the goal is to identify the characteristics that are considered important by the consumers when taking the decision of buying or using the products or services. When the survey is performed some characteristics that are present in the consumers population might not be reported by those consumers in the observed sample. Therefore, some important characteristics of the product according to the consumers opinions could be missing in the observed sample. The main objective of this paper is to show how the amount of characteristics missing in the observed sample could be easily estimated by using some Bayesian estimators proposed by Mingoti & Meeden (1992) and Mingoti (1999). An example of application related to an automobile survey is presented.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382001000100003species problemBayesian estimatorsmaximum likelihoodconsumers survey
collection DOAJ
language English
format Article
sources DOAJ
author Mingoti Sueli A.
spellingShingle Mingoti Sueli A.
HOW TO ESTIMATE THE AMOUNT OF IMPORTANT CHARACTERISTICS MISSING IN A CONSUMERS SAMPLE BY USING BAYESIAN ESTIMATORS
Pesquisa Operacional
species problem
Bayesian estimators
maximum likelihood
consumers survey
author_facet Mingoti Sueli A.
author_sort Mingoti Sueli A.
title HOW TO ESTIMATE THE AMOUNT OF IMPORTANT CHARACTERISTICS MISSING IN A CONSUMERS SAMPLE BY USING BAYESIAN ESTIMATORS
title_short HOW TO ESTIMATE THE AMOUNT OF IMPORTANT CHARACTERISTICS MISSING IN A CONSUMERS SAMPLE BY USING BAYESIAN ESTIMATORS
title_full HOW TO ESTIMATE THE AMOUNT OF IMPORTANT CHARACTERISTICS MISSING IN A CONSUMERS SAMPLE BY USING BAYESIAN ESTIMATORS
title_fullStr HOW TO ESTIMATE THE AMOUNT OF IMPORTANT CHARACTERISTICS MISSING IN A CONSUMERS SAMPLE BY USING BAYESIAN ESTIMATORS
title_full_unstemmed HOW TO ESTIMATE THE AMOUNT OF IMPORTANT CHARACTERISTICS MISSING IN A CONSUMERS SAMPLE BY USING BAYESIAN ESTIMATORS
title_sort how to estimate the amount of important characteristics missing in a consumers sample by using bayesian estimators
publisher Sociedade Brasileira de Pesquisa Operacional
series Pesquisa Operacional
issn 0101-7438
1678-5142
publishDate 2001-01-01
description Consumers surveys are conducted very often by many companies with the main objective of obtaining information about the opinions the consumers have about a specific prototype, product or service. In many situations the goal is to identify the characteristics that are considered important by the consumers when taking the decision of buying or using the products or services. When the survey is performed some characteristics that are present in the consumers population might not be reported by those consumers in the observed sample. Therefore, some important characteristics of the product according to the consumers opinions could be missing in the observed sample. The main objective of this paper is to show how the amount of characteristics missing in the observed sample could be easily estimated by using some Bayesian estimators proposed by Mingoti & Meeden (1992) and Mingoti (1999). An example of application related to an automobile survey is presented.
topic species problem
Bayesian estimators
maximum likelihood
consumers survey
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382001000100003
work_keys_str_mv AT mingotisuelia howtoestimatetheamountofimportantcharacteristicsmissinginaconsumerssamplebyusingbayesianestimators
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