Globular clusters are cosmological fossils, revealing the history of the universe and galaxies. Some galaxies are found to have multiple generations of globular clusters. Traditionally, these multiple epochs of cluster formation have been detected through graphical methods. In this presentation, we discuss statistical model selection to determine the number of components in globular cluster sys...

We consider selection of nested and non-nested semiparametric models. Using profile likelihood we can define both a likelihood ratio statistic and an Akaike information for models with nuisance parameters. Asymptotic quadratic expansion of the log profile likelihood allows derivation of the asymptotic null distribution of the likelihood ratio statistic including the boundary cases, as well as u...

The Akaike (1973, 1974) information criterion, AIC, and the corrected Akaike information criterion (Hurvich and Tsai, 1989), AICc, were both designed as estimators of the expected Kullback-Leibler discrepancy between the model generating the data and a tted candidate model. AIC is justiied in a very general framework, and as a result, ooers a crude estimator of the expected discrepancy: one whi...

By fitting dynamic contrast-enhanced MRI data to an appropriate pharmacokinetic model, quantitative physiological parameters can be estimated. In this study, we compare four different models by applying four statistical measures to assess their ability to describe dynamic contrast-enhanced MRI data obtained in 28 human breast cancer patient sets: the chi-square test (χ(2)), Durbin-Watson statis...

In Minimum Message Length (MML) clustering (unsupervised classification, mixture modelling) the aim is to infer a set of classes that best explains the observed data items. There are cases where parts of the observed data do not need to be explained by the inferred classes but can be used to improve the inference and resulting predictions. Our main contribution is to provide a simple and flexib...

Abstract. Many examples of calibration in climate science raise no alarms regarding model reliability. We examine one example and show that, in employing Classical Hypothesis-testing, it involves calibrating a base model against Many examples of calibration in climate science raise no alarms regarding model reliability. We examine one example and show that, in employing Classical Hypothesis-tes...

There are various methods for determining the moment at which a student has learned a given skill. Using the Akaike information criterion (AIC), we introduce an approach for determining the probability that an individual student has learned a given skill at a particular problem-solving step. We then investigate how well this approach works when applied to student log data. Using log data from s...

To determine the number of clusters in the clustering analysis that has a broad range of applied sciences, such as physics, chemistry, biology, engineering, economics etc., many methods have been proposed in the literature. The aim of this paper is to determine the number of clusters of a dataset in a model-based clustering by using an Analytic Hierarchy Process (AHP). In this study, the AHP mo...

The weighing records of 18 crossbred females with average live weight of 14.7 ± 3.14 kg were analyzed to study the relationship of the growth of crossbred hair sheep with some zoometric measures. The weight was established and took the measures thoracic perimeter, cannon perimeter, body length, neck length, hip amplitude, ischial amplitude, withers height and croup height. All parameters were s...

We propose an omnivariate decision tree architecture which contains univariate, multivariate linear or nonlinear nodes, matching the complexity of the node to the complexity of the data reaching that node. We compare the use of different model selection techniques including AIC, BIC, and CV to choose between the three types of nodes on standard datasets from the UCI repository and see that such...