Publications (12)
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…
Correlations between IR Luminosity, Star Formation Rate, and CO Luminosity in the Local Universe
Matteo Bonato, Ivano Baronchelli, Viviana Casasola +5
We exploit the DustPedia sample of galaxies within approximately 40 Mpc, selecting 388 sources, to investigate the correlations between IR luminosity (L), the star forma…
Using Planck maps for a systematic search of ultra-bright high-redshift strongly lensed galaxies
Matteo Bonato, Leonardo Trobbiani, Ivano Baronchelli +6
This paper presents a novel approach to the use of Planck telescope data for the systematic search of ultra-bright high-redshift strongly lensed galaxies. These galaxies provide cr…
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…
Objective Bayesian inference with proper scoring rules
Federica Giummolè, Valentina Mameli, Erlis Ruli +1
Standard Bayesian analyses can be difficult to perform when the full likelihood, and consequently the full posterior distribution, is too complex and difficult to specify or if rob…
Robust confidence distributions from proper scoring rules
Erlis Ruli, Laura Ventura, Monica Musio
A confidence distribution is a distribution for a parameter of interest based on a parametric statistical model. As such, it serves the same purpose for frequentist statisticians a…