maximum likelihood

Reduced-bias estimation of spatial autoregressive models with incompletely geocoded data

This contribution aims at developing a strategy to reduce the bias and produce more reliable inference for spatial models with location errors. The proposed estimation strategy models both the spatial stochastic process and the coarsening mechanism by means of a marked point process.

Testing a parameter restriction on the boundary for the g-and-h distribution: a simulated approach

We develop a likelihood-ratio test for discriminating between the g-and-h and the g distribution, which is a special case of the former obtained when the parameter h is equal to zero.