Despite its probable occurrence in Nature, the accretion-induced collapse (AIC) of a white dwarf (WD) has not yet been directly observed (or, at least, it has not been unambiguously identified as such). In this contribution we summarize the observational signatures of AIC, emphasizing its possible role as both an optical and high-energy transient. Due to the low quantity of ejected mass and rad...

Statistical thinking in wildlife biology and ecology has been profoundly influenced by the introduction of AIC (Akaike's information criterion) as a tool for model selection and as a basis for model averaging. In this paper, we advocate the Bayesian paradigm as a broader framework for multimodel inference, one in which model averaging and model selection are naturally linked, and in which the p...

The failure of the information-based Akaike Information Criterion (AIC) in the context of singular models can be rectified by the definition of a Frequentist Information Criterion (FIC). FIC applies a frequentist approximation to the computation of the model complexity, which can be estimated analytically in many contexts. Like AIC, FIC can be understood as an unbiased estimator of the model pr...

The Akaike Information Criterion, AIC (Akaike, 1973), and a bias-corrected version, Aicc (Sugiura, 1978; Hurvich & Tsai, 1989) are two methods for selection of regression and autoregressive models. Both criteria may be viewed as estimators of the expected Kullback-Leibler information. The bias of AIC and AICC is studied in the underfitting case, where none of the candidate models includes the t...

Plasmas with high ion-temperature of several keV and strong temperature anisotropy of more than 10 have been produced by using ion-cyclotron range of frequency (ICRF) heating in the GAMMA 10 tandem mirror. In such high performance plasmas with strong anisotropy, high-frequency fluctuations, so-called Alfvén-Ion-Cyclotron (AIC) waves, are spontaneously excited. The AIC waves have several discret...

The most commonly used model selection criterion, Akaike’s Information Criterion (AIC), cannot be used when the Generalized Estimating Equations (GEE) approach is considered for analyzing multivariate binary response. Recently, a modified version of AIC (mAIC) which is based on quasi-likelihood function is proposed as a model selection criterion. This model selection criterion can be used in th...

Autoimmune cholangitis (AIC) was first described in 1987 as immunocholangitis in three women who presented with signs and symptoms of primary biliary cholangitis (PBC), but who were antimitochondrial (AMA) negative and antinuclear antibodies (ANA) positive, and responded to immunosuppressive therapy with azathioprine and prednisolone (1). AIC is a rare chronic cholestatic inflammatory disease c...

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...