• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2017 Fiscal Year Final Research Report

How sparse are sparse trees, and why?

Research Project

  • PDF
Project/Area Number 16K12658
Research Category

Grant-in-Aid for Challenging Exploratory Research

Allocation TypeMulti-year Fund
Research Field Environmental policy and social systems
Research InstitutionKanazawa University

Principal Investigator

Kawanishi Takuya  金沢大学, 自然システム学系, 准教授 (80234087)

Project Period (FY) 2016-04-01 – 2018-03-31
Keywords統計 / 環境 / パラメーター推算
Outline of Final Research Achievements

We have been tried to develop methods for characterizing the sparse trees in arid region to facilitate the afforestation for carbon sequestration.
During the analysis of sparse trees, we came up with a new method of statistical parameter estimation. In the analysis of sparse trees, we concern the generalized extreme value distribution (GEV). For some range of parameters, the maximum likelihood (ML) method does not work for estimation of GEV parameters. Among the alternatives of ML, the method of maximum spacings (MPS) are convenient because it can be applied wider range of parameters and relatively small error of estimation.
Our method is a variant of MPS and it is in general less bias than MPS, and theoretical more proxy to ML.

Free Research Field

化学工学

URL: 

Published: 2019-03-29  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi