About: Maximum score estimator

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In statistics and econometrics, the maximum score estimator is a nonparametric estimator for discrete choice models developed by Charles Manski in 1975. Unlike the multinomial probit and multinomial logit estimators, it makes no assumptions about the distribution of the unobservable part of utility. However, its statistical properties (particularly its asymptotic distribution) are more complicated than the multinomial probit and logit models, making statistical inference difficult. To address these issues, proposed a variant, called the smoothed maximum score estimator.

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  • In statistics and econometrics, the maximum score estimator is a nonparametric estimator for discrete choice models developed by Charles Manski in 1975. Unlike the multinomial probit and multinomial logit estimators, it makes no assumptions about the distribution of the unobservable part of utility. However, its statistical properties (particularly its asymptotic distribution) are more complicated than the multinomial probit and logit models, making statistical inference difficult. To address these issues, proposed a variant, called the smoothed maximum score estimator. (en)
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  • In statistics and econometrics, the maximum score estimator is a nonparametric estimator for discrete choice models developed by Charles Manski in 1975. Unlike the multinomial probit and multinomial logit estimators, it makes no assumptions about the distribution of the unobservable part of utility. However, its statistical properties (particularly its asymptotic distribution) are more complicated than the multinomial probit and logit models, making statistical inference difficult. To address these issues, proposed a variant, called the smoothed maximum score estimator. (en)
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  • Maximum score estimator (en)
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