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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Sociedade Brasileira de Pesquisa Operacional
2001-01-01
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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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1725677096733245440 |