Liu-Type Multinomial Logistic Estimator
| Autor: | Mohamed R. Abonazel, Rasha A. Farghali |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Statistics and Probability
Mean squared error Applied Mathematics 05 social sciences Estimator Variance (accounting) Type (model theory) 01 natural sciences Confidence interval 010104 statistics & probability Multicollinearity 0502 economics and business Statistics Multinomial distribution 0101 mathematics Statistics Probability and Uncertainty 050205 econometrics Mathematics Multinomial logistic regression |
| Zdroj: | Sankhya B. 81:203-225 |
| ISSN: | 0976-8394 0976-8386 |
| DOI: | 10.1007/s13571-018-0171-4 |
| Popis: | Multicollinearity in multinomial logistic regression affects negatively on the variance of the maximum likelihood estimator. That leads to inflated confidence intervals and theoretically important variables become insignificant in testing hypotheses. In this paper, Liu-type estimator is proposed that has smaller total mean squared error than the maximum likelihood estimator. The proposed estimator is a general estimator which includes other biased estimators such as Liu estimator and ridge estimator as special cases. Simulation studies and an application are given to evaluate the performance of our estimator. The results indicate that the proposed estimator is more efficient and reliable than the conventional estimators. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink