Uncertainty in choice modeling

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(New page: Econometric models of consumer choice have been used to drive engineering optimization models toward profitable designs. However, there is an uncertainty in every model that must be accou...)
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Econometric models of consumer choice have been used to
Econometric models of consumer choice have been used to
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drive engineering optimization models toward profitable designs.  However, there is an uncertainty in every model that must be accounted for.  There are various statistical methods available for quantifying the uncertainty in these choice models in order to determine how the uncertainty affects design decisions.  The method of determining uncertainty depends on the method used to optimize the econometric model.  For most choice models, the method of maximum likelihood (ML) is used.  However, an introduction into the uncertainty associated with simpler ordinary least squares (OLS) methods yields insight into statistical methods such as hypothesis testing and determining confidence intervals, which are also useful for maximum likelihood estimation.
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drive engineering optimization models toward profitable designs.  However, there is uncertainty in every model that must be accounted for.  There are various statistical methods available for quantifying the uncertainty in these choice models in order to determine how the uncertainty affects design decisions.  The method of determining uncertainty depends on the method used to optimize the econometric model.  For most choice models, the method of maximum likelihood (ML) is used.  However, an introduction into the uncertainty associated with simpler ordinary least squares (OLS) methods yields insight into statistical methods such as hypothesis testing and determining confidence intervals, which are also useful for maximum likelihood estimation.

Revision as of 15:07, 15 February 2008

Econometric models of consumer choice have been used to drive engineering optimization models toward profitable designs. However, there is uncertainty in every model that must be accounted for. There are various statistical methods available for quantifying the uncertainty in these choice models in order to determine how the uncertainty affects design decisions. The method of determining uncertainty depends on the method used to optimize the econometric model. For most choice models, the method of maximum likelihood (ML) is used. However, an introduction into the uncertainty associated with simpler ordinary least squares (OLS) methods yields insight into statistical methods such as hypothesis testing and determining confidence intervals, which are also useful for maximum likelihood estimation.

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