hoa: An R package bundle for higher order likelihood inference. Performs likelihood-based inference for a wide range of regression models. Provides higher-order approximations for inference based on extensions of saddlepoint type arguments as discussed in the book Applied Asymptotics: Case Studies in Small-Sample Statistics by Brazzale, Davison, and Reid (2007).
Keywords for this software
References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Biehler, Martin; Holling, Heinz; Doebler, Philipp: Saddlepoint approximations of the distribution of the person parameter in the two parameter logistic model (2015)
- Ventura, Laura; Sartori, Nicola; Racugno, Walter: Objective Bayesian higher-order asymptotics in models with nuisance parameters (2013)
- Robinson, Andrew P.; Hamann, Jeff D.: Forest analytics with R (2011)
- Brazzale, Alessandra R.; Davison, Anthony C.: Accurate parametric inference for small samples (2008)