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researcher

H. Seya

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • stat.AP2
  • econ.EM1
  • stat.ME1

identity via Semantic Scholar / OpenAlex

activity
20172021
most citedPropensity score matching for multiple treatment levels: A CODA-based contribution

2 citations · 5 across the 3 of their papers we have counts for

collaborators

4 papers

stat.AP2021★ 1 cited

Spatial prediction of apartment rent using regression-based and machine learning-based approaches with a large dataset

Takahiro Yoshida, Hajime Seya

Employing a large dataset (at most, the order of n = 10^6), this study attempts enhance the literature on the comparison between regression and machine learning (ML)-based rent pri…

stat.AP2019★ 2 cited

A comparison of apartment rent price prediction using a large dataset: Kriging versus DNN

Hajime Seya, Daiki Shiroi

The hedonic approach based on a regression model has been widely adopted for the prediction of real estate property price and rent. In particular, a spatial regression technique ca…

stat.ME2018

Low rank spatial econometric models

Daisuke Murakami, Hajime Seya, Daniel A. Griffith

This article presents a re-structuring of spatial econometric models in a linear mixed model framework. To that end, it proposes low rank spatial econometric models that are robust…

econ.EM2017★ 2 cited

Propensity score matching for multiple treatment levels: A CODA-based contribution

Hajime Seya, Takahiro Yoshida

This study proposes a simple technique for propensity score matching for multiple treatment levels under the strong unconfoundedness assumption with the help of the Aitchison dista…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.