The curve-fitting problem is often viewed as an exemplar which encapsulates the multitude of dimensions and issues associated with inductive inference, including underdetermination and the reliability of inference. The prevailing view is that the ‘fittest’ curve is one which provides the optimal trade-off between goodness-of-fit and simplicity, with the Akaike Information Criterion (AIC) the pr...

To perform a comprehensive analysis comparing the prognostic and discriminative ability of the eighth AJCC gastric cancer (GC) pathological classification to that of the seventh, sixth and fifth editions, and secondly to assess their long-term significance. Patients who had undergone R0 gastrectomy were identified and restaged accordingly. To evaluate and confirm any difference in prognostic ab...

Our goal is to represent a given 2D shape with an automatically determined number of ellipses, so that the total area covered by the ellipses is equal to the area of the original shape without any assumption or prior knowledge about the object structure. To solve this interesting theoretical problem, first we employ the skeleton of the 2D shape which provides important information on the parame...

The selection of a best-subset regression model from a candidate family is a common problem that arises in many analyses. In best-subset model selection, we consider all possible subsets of regressor variables; thus, numerous candidate models may need to be fit and compared. One of the main challenges of best-subset selection arises from the size of the candidate model family: specifically, the...

I show how one can estimate the shape of a thermal performance curve using information theory. This approach ranks plausible models by their Akaike information criterion (AIC), which is a measure of a model’s ability to describe the data discounted by the model’s complexity. I analyze previously published data to demonstrate how one applies this approach to describe a thermal performance curve....

Accurate state of charge (SoC) estimation of batteries plays an important role in promoting the commercialization of electric vehicles. The main work to be done in accurately determining battery SoC can be summarized in three parts. (1) In view of the model-based SoC estimation flow diagram, the n-order resistance-capacitance (RC) battery model is proposed and expected to accurately simulate th...

Membrane proteins move in heterogeneous environments with spatially (sometimes temporally) varying friction and with biochemical interactions with various partners. It is important to reliably distinguish different modes of motion to improve our knowledge of the membrane architecture and to understand the nature of interactions between membrane proteins and their environments. Here, we present ...

One of the important challenges of microarray analysis is the identification of tissue-specific genes whose expression profile is considerably different in particular tissue(s) than in others. Those characteristics facilitate the identification of a large number of possible markers. In general, the problem of identifying tissue-specific expression patterns in multisource data can be viewed as a...

Statistical models for the evolution of molecular sequences play an important role in the study of evolutionary processes. For the evolutionary analysis of protein-coding sequences, 3 types of evolutionary models are available: 1) nucleotide, 2) amino acid, and 3) codon substitution models. Selecting appropriate models can greatly improve the estimation of phylogenies and divergence times and t...

The data driven Neyman statistic consists of two elements: a score statistic in a finite dimensional submodel and a selection rule to determine the best fitted submodel. For instance, Schwarz BIC and Akaike AIC rules are often applied in such constructions. For moderate sample sizes AIC is sensitive in detecting complex models, while BIC works well for relatively simple structures. When the sam...