5 papers
On the use of the cumulant generating function for inference on time series
Alban Moor, Davide La Vecchia, Elvezio Ronchetti
We introduce innovative inference procedures for analyzing time series data. Our methodology enables density approximation and composite hypothesis testing based on Whittle's estim…
Semiparametric Approach to Estimation of Marginal and Quantile Effects
Seong-ho Lee, Yanyuan Ma, Elvezio Ronchetti
We consider a semiparametric generalized linear model and study estimation of both marginal and quantile effects in this model. We propose an approximate maximum likelihood estimat…
New Bias Calibration for Robust Estimation in Small Areas
Setareh Ranjbar, Elvezio Ronchetti, Stefan Sperlich
Using sample surveys as a cost effective tool to provide estimates for characteristics of interest at population and sub-populations (area/domain) level has a long tradition in "sm…
Saddlepoint approximations for spatial panel data models
Chaonan Jiang, Davide La Vecchia, Elvezio Ronchetti +1
We develop new higher-order asymptotic techniques for the Gaussian maximum likelihood estimator in a spatial panel data model, with fixed effects, time-varying covariates, and spat…
Composite Likelihood Inference by Nonparametric Saddlepoint Tests
Nicola Lunardon, Elvezio Ronchetti
The class of composite likelihood functions provides a flexible and powerful toolkit to carry out approximate inference for complex statistical models when the full likelihood is e…