23 citations · 29 across the 8 of their papers we have counts for
8 papers
The Group Lasso for Design of Experiments
Kentaro Tanaka, Masami Miyakawa
We introduce an application of the group lasso to design of experiments. Note that we are NOT trying to explain experimental design for the group lasso. Conversely, we explain how…
Cones of elementary imsets and supermodular functions: a review and some new results
Takuya Kashimura, Tomonari Sei, Akimichi Takemura +1
In this paper we give a review of the method of imsets introduced by Studeny (2005) from a geometric point of view. Elementary imsets span a polyhedral cone and its dual cone is th…
Properties of semi-elementary imsets as sums of elementary imsets
Takuya Kashimura, Tomonari Sei, Akimichi Takemura +1
We study properties of semi-elementary imsets and elementary imsets introduced by Studeny (2005). The rules of the semi-graphoid axiom (decomposition, weak union and contraction) f…
Application of Mathematical Optimization Procedures to Intervention Effects in Structural Equation Models
Kentaro Tanaka, Atsushi Yagishita, Masami Miyakawa
For a given statistical model, it often happens that it is necessary to intervene the model to reduce the variances of the output variables. In structural equation models, this can…
Strong consistency of the maximum likelihood estimator for finite mixtures of location-scale distributions when penalty is imposed on the ratios of the scale parameters
Kentaro Tanaka
In finite mixtures of location-scale distributions, if there is no constraint or penalty on the parameters, then the maximum likelihood estimator does not exist because the likelih…
Strong consistency of MLE for finite mixtures of location-scale distributions when the ratios of the scale parameters are exponentially small
Kentaro Tanaka
In finite mixtures of location-scale distributions, if there is no constraint on the parameters then the maximum likelihood estimate does not exist. But when the ratios of the scal…
Strong consistency of MLE for finite mixtures of location-scale distributions when the scale parameters are exponentially small (full version)
Kentaro Tanaka, Akimichi Takemura
In a finite mixture of location-scale distributions maximum likelihood estimator does not exist because of the unboundedness of the likelihood function when the scale parameter of…
Strong consistency of MLE for finite uniform mixtures when the scale parameters are exponentially small
Kentaro Tanaka, Akimichi Takemura
We consider maximum likelihood estimation of finite mixture of uniform distributions. We prove that maximum likelihood estimator is strongly consistent, if the scale parameters of…