LBI-package: Likelihood Based Inference

In LBI: Likelihood Based Inference

Likelihood Based Inference

Description

It conducts likelihood based inference.

Details

Modern likelihood concept and maximum likelihood estimation are established by Fisher RA, while Likelihood Ratio Test (LRT) is established by Neyman J. Post-Fisher methods - generalized linear model, survival analysis, and mixed effects model - are all likelihood based. Inferences from the perspective of Fisherian and pure likelihoodist are suggested here.

Author(s)

Kyun-Seop Bae <[e-mail]>

References

1. Wilks SS. The Large-sample Distribution of the Likelihood Ratio for Testing Composite Hypotheses. Ann Math Stat. 1938;9(1):60-62.

2. Edwards AWF. Likelihood. 1972.

3. Fisher RA. Statistical Methods and Scientific Inference. 3e. 1973.

4. Bates DM, Watts DG. Nonlinear Regression Analysis and its Application. 1988.

5. Ruppert D, Cressie N, Carroll RJ. A Transformation/Weighting Model for Estimating Michaelis-Menten Parameters. Cornell University Technical Report 796. 1988.

6. Royall R. Statistical Evidence. 1997.

7. Pinheiro JC, Bates DM. Mixed Effects Models in S and S-PLUS. 2000.

8. Pawitan Y. In All Likelihood: Statistical Modelling and Inference Using Likelihood. 2001.

9. Lehmann EL. Fisher, Nayman, and the Creation of Classical Statistics. 2011.

10. Rohde CA. Introductory Statistical Inference with the Likelihood Function. 2014.

11. Held L, Bove DS. Likelihood and Bayesian Inference. 2020.

LBI documentation built on Oct. 17, 2024, 9:06 a.m.