Search results for "likelihood"
showing 10 items of 264 documents
Widespread secondary contact and new glacial refugia in the halophilic rotifer Brachionus plicatilis in the Iberian Peninsula.
2011
Small aquatic organisms harbour deep phylogeographic patterns and highly structured populations even at local scales. These patterns indicate restricted gene flow, despite these organisms' high dispersal abilities, and have been explained by a combination of (1) strong founder effects due to rapidly growing populations and very large population sizes, and (2) the development of diapausing egg banks and local adaptation, resulting in low effective gene flow, what is known as the Monopolization hypothesis. In this study, we build up on our understanding of the mitochondrial phylogeography of the halophilic rotifer Brachionus plicatilis in the Iberian Peninsula by both increasing the number of…
Semi-parametric estimation of the intensity function in space-time point processes
2009
Occlusion-based estimation of independent multinomial random variables using occurrence and sequential information
2017
Abstract This paper deals with the relatively new field of sequence-based estimation in which the goal is to estimate the parameters of a distribution by utilizing both the information in the observations and in their sequence of appearance. Traditionally, the Maximum Likelihood (ML) and Bayesian estimation paradigms work within the model that the data, from which the parameters are to be estimated, is known, and that it is treated as a set rather than as a sequence. The position that we take is that these methods ignore, and thus discard, valuable sequence -based information, and our intention is to obtain ML estimates by “extracting” the information contained in the observations when perc…
An experience in pedigree reconstruction based on likelihood methods using genetic markers
2007
Completing the logarithmic scoring rule for assessing probability distributions
2012
We propose and motivate an expanded version of the logarithmic score for forecasting distributions, termed the Total Log score. It incorporates the usual logarithmic score, which is recognised as incomplete and has been mistakenly associated with the likelihood principle. The expectation of the Total Log score equals the Negentropy plus the Negextropy of the distribution. We examine both discrete and continuous forms of the scoring rule, and we discuss issues of scaling for scoring assessments. The analysis suggests the dual tracking of the quadratic score along with the usual log score when assessing the qualities of probability distributions. An application to the sequential scoring of f…
Semiparametric estimation of conditional intensity functions for space-time processes
2008
When dealing with data coming from a space time inhomogeneous process, there is often the need of obtaining reliable estimates of the conditional intensity function. According to the field of application, intensity function can be estimated through some assessed parametric model, where parameters are estimated by Maximum Likelihood method. If we are only in an exploratory context or we would like to assess the adequacy of the parametric model, some kind of nonparametric estimation is required. Often, isotropic or anisotropic kernel estimates can be used, e.g. using the Silverman rule for the choice of the windows sizes h (Silverman, 1986). When the purpose of the study is the estimation of …
The age and evolution of sociality in Stegodyphus spiders: a molecular phylogenetic perspective
2006
Social, cooperative breeding behaviour is rare in spiders and generally characterized by inbreeding, skewed sex ratios and high rates of colony turnover, processes that when combined may reduce genetic variation and lower individual fitness quickly. On these grounds, social spider species have been suggested to be unstable in evolutionary time, and hence sociality a rare phenomenon in spiders. Based on a partial molecular phylogeny of the genus Stegodyphus , we address the hypothesis that social spiders in this genus are evolutionary transient. We estimate the age of the three social species, test whether they represent an ancestral or derived state and assess diversification relative to s…
Modeling Forest Tree Data Using Sequential Spatial Point Processes
2021
AbstractThe spatial structure of a forest stand is typically modeled by spatial point process models. Motivated by aerial forest inventories and forest dynamics in general, we propose a sequential spatial approach for modeling forest data. Such an approach is better justified than a static point process model in describing the long-term dependence among the spatial location of trees in a forest and the locations of detected trees in aerial forest inventories. Tree size can be used as a surrogate for the unknown tree age when determining the order in which trees have emerged or are observed on an aerial image. Sequential spatial point processes differ from spatial point processes in that the…
An association model for bivariate data with application to the anlysis of university students' success.
2015
The academic success of students is a priority for all universities. We analyze the students' success at university by considering their performance in terms of both ‘qualitative performance’, measured by their mean grade, and ‘quantitative performance’, measured by university credits accumulated. These data come from an Italian University and concern a cohort of students enrolled at the Faculty of Economics. To jointly model both the marginal relationships and the association structure with covariates, we fit a bivariate ordered logistic model by penalized maximum likelihood estimation. The penalty term we use allows us to smooth the association structure and enlarge the range of possible …
A penalized approach for the bivariate ordered logistic model with applications to social and medical data
2018
Bivariate ordered logistic models (BOLMs) are appealing to jointly model the marginal distribution of two ordered responses and their association, given a set of covariates. When the number of categories of the responses increases, the number of global odds ratios to be estimated also increases, and estimation gets problematic. In this work we propose a non-parametric approach for the maximum likelihood (ML) estimation of a BOLM, wherein penalties to the differences between adjacent row and column effects are applied. Our proposal is then compared to the Goodman and Dale models. Some simulation results as well as analyses of two real data sets are presented and discussed.