Search results for "second-order"

Flexible space-time process for seismic data

2009

Point processes are well studied objects in probability theory and a powerful tool in statistics for modelling and analyzing the distribution of real phenomena, such as the seismic one. Point processes can be specified mathematically in several ways, for instance, by considering the joint distributions of the counts of points in arbitrary sets or defining a complete intensity function. The conditional intensity function is a function of the point history and it is itself a stochastic process depending on the past up to time t. In this paper some techniques to estimate the intensity function of space-time point processes are developed, by following semi-parametric approaches and diagnostic m…

Reasons and freedom

2015

En este artículo, tengo la intención de defender el libertarismo contra la llamada "objeción de la suerte”, según la cual una elección causalmente indeterminada es puramente afortunada o arbitraria, y por lo tanto no es algo que un agente pueda controlar y ser moralmente responsable. Trato de responder a esta objeción sobre la base de una reflexión sobre si la deliberación es una cuestión de sopesar razones o de darles peso. Con este fin, me baso en algunas ideas de P. Greenspan y J. Raz. Trato de defender el modelo de dar peso contra las acusaciones de irracionalidad. Sostengo, en primer lugar, que dar peso a las razones es un proceso indispensable en ciertos casos, en el que las razones q…

Community detection of seismic point processes

2022

In this paper, we combine robin and Local Indicators of Spatio-Temporal Association (LISTA) functions. robin is an R package to assess the robustness of the community structure of a network found by one or more methods to give indications about their reliability. We use it to propose a classification algorithm of events in a spatio-temporal point pattern, by means of the local second-order characteristics and the community detection procedure in network analysis. We demonstrate the proposed procedure on a real data analysis on seismic data.

Student engagement, truancy, and cynicism : a longitudinal study from primary school to upper secondary education

2021

Truancy in upper secondary education is a widespread problem, which contributes significantly to school dropout risk. However, the underlying mechanisms of truancy have remained unstudied. This longitudinal study of 1853 Finnish students examined how initial levels and changes in student engagement from primary (Grade 6) to lower secondary school (Grades 7 and 9) predicted truancy in upper secondary education, and whether cynicism (losing interest in school) mediated the relationship between engagement and truancy. Growth curve models showed that high engagement levels in primary school and increases in engagement over time predicted less truancy in upper secondary education. Cynicism media…

A black-box, general purpose quadratic self-consistent field code with and without Cholesky Decomposition of the two-electron integrals

2021

We present the implementation of a quadratically convergent self-consistent field (QCSCF) algorithm based on an adaptive trust-radius optimisation scheme for restricted open-shell Hartree���Fock (ROHF), restricted Hartree���Fock (RHF), and unrestricted Hartree���Fock (UHF) references. The algorithm can exploit Cholesky decomposition (CD) of the two-electron integrals to allow calculations on larger systems. The most important feature of the QCSCF code lies in its black-box nature ��� probably the most important quality desired by a generic user. As shown for pilot applications, it does not require one to tune the self-consistent field (SCF) parameters (damping, Pulay's DIIS, and other simil…

Models and methods for space and space-time interactions in complex point processes with applications on earthquakes

Local methods for complex spatio-temporal point processes

2022

Weighted local second-order statistics for complex spatio-temporal point processes

2019

Spatial, temporal, and spatio-temporal point processes, and in particular Poisson processes, are stochastic processes that are largely used to describe and model the distribution of a wealth of real phenomena. When a model is fitted to a set of random points, observed in a given multidimensional space, diagnostic measures are necessary to assess the goodness-of-fit and to evaluate the ability of that model to describe the random point pattern behaviour. The main problem when dealing with residual analysis for point processes is to find a correct definition of residuals. Diagnostics of goodness-of-fit in the theory of point processes are often considered through the transformation of data in…