Uncertain Johnson-Schumacher growth model with imprecise observations and \(k\)-fold cross-validation test
type: Item
instance of: scholarly article
title: Uncertain Johnson-Schumacher growth model with imprecise observations and \(k\)-fold cross-validation test
zbMATH Open document ID: 1436.62368
author: Liang Fang
author: Shiqin Liu
author: Zhiyong Huang
published in: Soft Computing
publication date: 2020-07-16T00:00:00Z
Mathematics Subject Classification ID: 62J86
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62M20
zbMATH DE Number: 7221908
zbMATH Keywords: regression analysis
zbMATH Keywords: Johnson-Schumacher growth model
zbMATH Keywords: uncertainty theory
zbMATH Keywords: uncertain variable
zbMATH Keywords: \(k\)-fold cross-validation
MaRDI profile type: Publication
full work available at URL: s00500-019-04090-4
OpenAlex ID: W2946911180
cites work: Least-squares estimates in fuzzy regression analysis.
cites work: Uncertainty theory
cites work: Uncertain multivariable regression model
cites work: Uncertain variance of sample and its application
cites work: Uncertain time series analysis with imprecise observations
cites work: A formula to calculate the variance of uncertain variable
cites work: Uncertain regression analysis: an approach for imprecise observations
Wikidata QID: Q127803655
DOI: 10.1007/S00500-019-04090-4
description: scientific article; zbMATH DE number 7221908