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20242026
most citedML, PL, QL in Markov chain models

40 citations · 118 across the 32 of their papers we have counts for

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14 papers · 1 filter

math.ST202616 cited

On multiplicative bias correction in kernel density estimation

M. C. Jones, D. F. Signorini, Nils Lid Hjort

Hjort and Glad (1995) present a method for semiparametric density estimation. Relative to the ordinary kernel density estimator, this technique performs much better when a parametr…

math.ST202610 cited

Bayesian and Empirical Bayesian Bootstrapping

Nils Lid Hjort

Let be a random sample from an unknown probability distribution on the sample space , and let be a parameter of interest. The present pape…

math.ST2026

Bayesian approaches to non- and semiparametric density estimation [with a rejoinder to my discussants]

Nils Lid Hjort

This invited paper proposes and discusses several Bayesian attempts at nonparametric and semiparametric density estimation. The main categories of these ideas are as follows: 1) Bu…

math.ST202614 cited

Bayesian analysis for a generalised Dirichlet process prior

Nils Lid Hjort

A family of random probabilities is defined and studied. This family contains the Dirichlet process as a special case, corresponding to an inner point in the appropriate parameter…

math.ST2026

A note on kernel density estimators with optimal bandwidths

Nils Lid Hjort, Stephen G. Walker

We show that the cumulative distribution function corresponding to a kernel density estimator with optimal bandwidth lies outside any confidence interval, around the empirical dist…

math.ST2026

Sometimes nonparametrics beat parametrics, even when the model is right

Morten Byholt, Nils Lid Hjort

A basic issue in both teaching of and practice of statistics is the interplay between modelling assumptions and inference performance. The general message conveyed is that stronger…