DIAPLAN is a language for programming with graphs representing diagrams that is currently being developed. The computational model of the languages, nested graph transformation, supports nested structuring of graphs, and graph variables, but is—hopefully—still intuitive. This paper is about structural typing of nested graphs and nested graph transformation systems by shape rules. We extend the ...

Many regression problems exhibit a natural grouping among predictor variables. Examples are groups of dummy variables representing categorical variables, or present and lagged values of time series data. Since model selection in such cases typically aims for selecting groups of variables rather than individual covariates, an extension of the popular least angle regression (LARS) procedure to gr...

The purpose of this research is to discuss Japanese financial instability and both private life insurance and public life insurance (Kampo) demand. At the same time, we also consider Kampo’s main role and what Kampo should be as an insurance service provider in the future. From empirically estimating private life insurance and Kampo demand functions using household-level data provided by the Po...

In this article, we study the problem of finding a singleton attractor for several biologically important subclasses of Boolean networks (BNs). The problem of finding a singleton attractor in a BN is known to be NP-hard in general. For BNs consisting of n nested canalyzing functions, we present an O(1.799(n)) time algorithm. The core part of this development is an O(min(2(k/2) · 2(m/2), 2(k)) ·...

A household vehicle transactions model has been developed as a competing risks duration model in this study. The model is developed assuming the following three types of competing risks: replacing one of the vehicles in the household fleet, disposing of one vehicle in the fleet, and acquiring one vehicle to add to the fleet. In addition to the attributes of household, changes in household attri...

Conditional random fields maximize the log-likelihood of training labels given the training data, e.g., objects given images. In many cases the training labels are structures that consist of a set of variables and the computational complexity for estimating their likelihood is exponential in the number of the variables. Learning algorithms relax this computational burden using approximate infer...

This paper is concerned with methods that automatically prove termination of term rewrite systems. The aim of dummy elimination, a method to prove termination introduced by Ferreira and Zantema, is to transform a given rewrite system into a rewrite system whose termination is easier to prove. We show that dummy elimination is subsumed by the more recent dependency pair method of Arts and Giesl....

The nested logit model has been widely used to study nested choice. A typical example of such nested choice is store patronage and brand choice. An important limitation of the nested logit model is that it assumes that all alternatives at both levels of the nest are available in the choice set of the consumer. While there is a wide literature on the incorporation of restricted choice sets into ...