25 citations · 65 across the 11 of their papers we have counts for
4 papers · 1 filter
On Model Selection with Summary Statistics
Erlis Ruli
Recently, many authors have cast doubts on the validity of ABC model choice. It has been shown that the use of sufficient statistic in ABC model selection leads, apart from few exc…
Improved Laplace Approximation for Marginal Likelihoods
Erlis Ruli, Nicola Sartori, Laura Ventura
Statistical applications often involve the calculation of intractable multidimensional integrals. The Laplace formula is widely used to approximate such integrals. However, in high…
Approximate Bayesian Computation with composite score functions
Erlis Ruli, Nicola Sartori, Laura Ventura
Both Approximate Bayesian Computation (ABC) and composite likelihood methods are useful for Bayesian and frequentist inference, respectively, when the likelihood function is intrac…
A note on marginal posterior simulation via higher-order tail area approximations
Erlis Ruli, Nicola Sartori, Laura Ventura
We explore the use of higher-order tail area approximations for Bayesian simulation. These approximations give rise to an alternative simulation scheme to MCMC for Bayesian computa…