maximum likelihood estimators造句
例句與造句
- The maximum likelihood estimator in logistic regression is a GP.
- Is there a way to use maximum likelihood estimators between two variables?
- M-estimators are a generalization of maximum likelihood estimators ( MLEs ).
- A maximum likelihood estimator coincides with the parameters.
- The Ma-Sandri-Sarkar maximum likelihood estimator is currently the best known estimator.
- It's difficult to find maximum likelihood estimators in a sentence. 用maximum likelihood estimators造句挺難的
- Maximum likelihood estimators ( MLE ) are thus a special case of M-estimators.
- NLOGIT is a full information maximum likelihood estimator for a variety of multinomial choice models.
- Another estimator which is asymptotically normal and efficient is the maximum likelihood estimator ( MLE ).
- This can be solved by iteration, and the maximum likelihood estimator for \ pi is given by
- Also, while the maximum likelihood estimator is asymptotically efficient, it is relatively inefficient for small samples.
- The maximum likelihood estimator only exists for samples for which the sample variance is larger than the sample mean.
- For many models, a maximum likelihood estimator can be found as an explicit function of the observed data.
- Maximum spacing estimators are also at least as asymptotically efficient as maximum likelihood estimators, where the latter exist.
- Thus the Bayesian estimator coincides with the maximum likelihood estimator for a uniform prior distribution P ( \ theta ).
- Takeshi Amemiya ( 1973 ) has proven that the maximum likelihood estimator suggested by Tobin for this model is consistent.
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