ﻻ يوجد ملخص باللغة العربية
The joint likelihood is a simple extension of the standard likelihood formalism that enables the estimation of common parameters across disjoint datasets. Joining the likelihood, rather than the data itself, means nuisance parameters can be dealt with independently. Application of this technique, particularly to Fermi-LAT dwarf spheroidal analyses, has already been met with great success. We present a description of the methods general implementation along with a toy Monte-Carlo study of its properties and limitations.
Evidence for an extraterrestrial flux of high-energy neutrinos has now been found in multiple searches with the IceCube detector. The first solid evidence was provided by a search for neutrino events with deposited energies $gtrsim30$ TeV and interac
A search for astrophysical point-like neutrino sources using the data collected by the ANTARES detector between January 29, 2007 and December 31, 2017 is presented. A likelihood stacking method is used to assess the significance of an excess of muon
During the last decade Levy processes with jumps have received increasing popularity for modelling market behaviour for both derviative pricing and risk management purposes. Chan et al. (2009) introduced the use of empirical likelihood methods to est
The extragalactic background light (EBL) is the radiation accumulated through the history of the Universe in the wavelength range from the ultraviolet to the far infrared. Local foregrounds make the direct measurement of the diffuse EBL notoriously d
We derive Laplace-approximated maximum likelihood estimators (GLAMLEs) of parameters in our Graph Generalized Linear Latent Variable Models. Then, we study the statistical properties of GLAMLEs when the number of nodes $n_V$ and the observed times of