Local likelihood density estimation based on smooth truncation

Local likelihood density estimation based on smooth truncation

Two existing density estimators based on local likelihood have properties that are comparable to those of local likelihood regression but they are much less used than their counterparts in regression. We consider truncation as a natural way of localising parametric density estimation. Based on this idea, a third local likelihood density estimator is introduced. Our main result establishes that ...

On Local Likelihood Density Estimation When the Bandwidth Is Large

In this paper, we provide a large bandwidth analysis for a class of local likelihood methods. This work complements the small bandwidth analysis of Park, Kim and Jones (2002). Our treatment is more general than the large bandwidth analysis of Eguchi and Copas (1998). We provide a higher order asymptotic analysis for the risk of the local likelihood density estimator, from which a direct compari...

Penalized Likelihood Density Estimation :

Logspline Density Estimation under Censoring and Truncation

In this paper we consider logspline density estimation for data that may be lefttruncated or right-censored. For randomly left-truncated and right-censored data the product-limit estimator is known to be a consistent estimator of the survivor function, having a faster rate of convergence than many density estimators. The product-limit estimator and B-splines are used to construct the logspline ...

Nonparametric maximum likelihood estimation for dependent truncation data based on copulas