We evaluate the performance of autoregressive, fractionally integrated, moving average (ARFIMA) modelling for detecting long-range dependence and estimating fractal exponents. More specifically, we test the procedure proposed by Wagenmakers, Farrell, and Ratcliff, and compare the results obtained with the Akaike information criterion (AIC) and the Bayes information criterion (BIC). The present ...

We carried out a discriminant analysis with identity by descent (mD) at each marker as inputs, and the sib pair type ( affected-affected versus affectedunaffected) as the output. Using simple logistic regression for this discriminant analysis, we illustrate the importance of comparing models with different number of parameters. Such model comparisons are best carried out using either the Akaike...

Ecologists are increasingly applying model selection to their data analyses, primarily to compare regression models. Model selection can also be used to compare mechanistic models derived from ecological theory, thereby providing a formal framework for testing the theory. The Akaike Information Criterion (AIC) is the most commonly adopted criterion used to compare models; however, its performan...

Abstract. To determine the exact shape of the luminosity function (LF) of galaxies is one of the central problems in galactic astronomy and observational cosmology. The most popular method to estimate the LF is maximum likelihood, which is clearly understood with the concepts of the information theory. In the field of information theory and statistical inference, great advance has been made by ...

In linear mixed models, the Akaike information criterion (AIC) is often used to decide on the inclusion of a random effect. An important special case is the choice between linear and nonparametric regression models estimated using mixed model penalized splines. We investigate the behavior of two commonly used versions of the AIC, derived either from the implied marginal model or the conditional...

In this paper I present a Minimum Description Length Estimator for number of sources in an anechoic mixture of sparse signals. The criterion is roughly equal to the sum of negative normalized maximum log-likelihood and the logarithm of number of sources. Numerical evidence supports this approach and compares favorabily to both the Akaike (AIC) and Bayesian (BIC) Information Criteria. 1 Signal a...

A multivariate distribution can be represented in terms of its underlying margins by binding these margins together using a copula function (Sklar, 1959). Here, we propose a new class of survival FGM type modification truncated copulas which quantify dependency and incorporate directional dependence. In addition, we apply our proposed methods to the analysis of directional dependence relationsh...

The information of first-arrival time of acoustic emission (AE) signal is important in event location, event identification and source mechanism analysis. Manual picks are time-consuming and sometimes subjective. Several approaches are used in practice. New first arrival automatic determination technique of AE signals in thin metal plates is presented. Based on Akaike information criterion (AIC...

The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness ...