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ABSTRACT The purpose of this study was to inform the continued development and refinement of the Resilience Education Program (REP), a Tier 2 targeted intervention for students in grades 4–8 exhibiting early signs of internalizing problems. Parents (n = 7), teachers (n = 7), school mental health professionals (n = 11), and researchers (n = 6 ...
Stephen Kilgus +7 more
wiley +1 more source
On the maximum likelihood degree of Gaussian graphical models
Abstract In this paper we revisit the likelihood geometry of Gaussian graphical models. We give a detailed proof that the ML‐degree behaves monotonically on induced subgraphs. Furthermore, we complete a missing argument that the ML‐degree of the nth$n{\rm th}$ cycle is larger than 1 for any n⩾4$n\geqslant 4$, therefore completing the characterization ...
Carlos Améndola +3 more
wiley +1 more source
Adaptive quantum kernel selection via leakage-free stacking for clinical diagnostics on NISQ hardware. [PDF]
Daga M +4 more
europepmc +1 more source
Finite-time and predefined-time dynamical systems for solving strongly pseudomonotone mixed equilibrium problems. [PDF]
Wen Q, Khan VK, Cai QB, Ahmad MK.
europepmc +1 more source
From Dirac Structures to Port-Hamiltonian Partial Differential Equations, a Tutorial Introduction. [PDF]
Zwart H.
europepmc +1 more source
Non-commutative structures of brain and cognition: quantum and contextual probability as a translational framework. [PDF]
Emori H, Khrennikov A, Iriki A.
europepmc +1 more source
Occupancy Statistics and Entropy in Bose Systems. [PDF]
Spalvieri A.
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Australian & New Zealand Journal of Statistics, 2014
SummaryA Bayes linear space is a linear space of equivalence classes of proportional σ‐finite measures, including probability measures. Measures are identified with their density functions. Addition is given by Bayes' rule and substraction by Radon–Nikodym derivatives. The present contribution shows the subspace of square‐log‐integrable densities to be
Boogaart, K. Gerald van den +2 more
openaire +3 more sources
SummaryA Bayes linear space is a linear space of equivalence classes of proportional σ‐finite measures, including probability measures. Measures are identified with their density functions. Addition is given by Bayes' rule and substraction by Radon–Nikodym derivatives. The present contribution shows the subspace of square‐log‐integrable densities to be
Boogaart, K. Gerald van den +2 more
openaire +3 more sources

