Comparison of parametric and nonparametric methods for modeling height-diameter relationships

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43410%2F17%3A43910797" target="_blank" >RIV/62156489:43410/17:43910797 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.3832/ifor1928-009" target="_blank" >https://doi.org/10.3832/ifor1928-009</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3832/ifor1928-009" target="_blank" >10.3832/ifor1928-009</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of parametric and nonparametric methods for modeling height-diameter relationships

Popis výsledku v původním jazyce

This paper focuses on the problem of regionalization of the height-diameter model at the stand level. To this purpose, we selected two different modeling techniques. As a parametric method, we chose a linear mixed effects model (LME) with calibrated conditional prediction, whose calibration was carried out on randomly selected trees either close to mean diameter or within three diameter intervals throughout the diameter range. As a nonparametric method, the technique of classification and regression trees (CART) was chosen. These two methods were also compared with the local model created by ordinary least squares regression. The results show that LME with calibrated conditional prediction based on measurements of height at three diameter intervals provided results very close to the local model, especially when six to nine trees are measured. We recommend this technique for the regionalization of the global model. The CART method provided worse results than LME, with the exception of parameters of the residual distribution. Nevertheless, the latter approach is very user-friendly, as the regression tree creation and especially its interpretation are relatively simple, and could be recommended when larger deviations are allowed.

Název v anglickém jazyce

Comparison of parametric and nonparametric methods for modeling height-diameter relationships

Popis výsledku anglicky

This paper focuses on the problem of regionalization of the height-diameter model at the stand level. To this purpose, we selected two different modeling techniques. As a parametric method, we chose a linear mixed effects model (LME) with calibrated conditional prediction, whose calibration was carried out on randomly selected trees either close to mean diameter or within three diameter intervals throughout the diameter range. As a nonparametric method, the technique of classification and regression trees (CART) was chosen. These two methods were also compared with the local model created by ordinary least squares regression. The results show that LME with calibrated conditional prediction based on measurements of height at three diameter intervals provided results very close to the local model, especially when six to nine trees are measured. We recommend this technique for the regionalization of the global model. The CART method provided worse results than LME, with the exception of parameters of the residual distribution. Nevertheless, the latter approach is very user-friendly, as the regression tree creation and especially its interpretation are relatively simple, and could be recommended when larger deviations are allowed.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40102 - Forestry

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

iForest

ISSN

1971-7458

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

February

Stát vydavatele periodika

IT - Italská republika

Počet stran výsledku

8

Strana od-do

1-8

Kód UT WoS článku

000395862000001

EID výsledku v databázi Scopus

2-s2.0-85011846574