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Volumn 12, Issue 5-7, 2001, Pages 373-384

Identifying random-scoring respondents in sensory research using finite mixture regression models

Author keywords

Latent class models; Mixture regression; Random scoring; Sensory assessment

Indexed keywords


EID: 0041878879     PISSN: 09503293     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0950-3293(01)00028-3     Document Type: Article
Times cited : (21)

References (6)
  • 1
    • 34250108028 scopus 로고
    • Model selection and Akaike's information criterion (AIC). the general theory and its analytical extensions
    • Bozdogan H. Model selection and Akaike's information criterion (AIC). The general theory and its analytical extensions. Psychometrika. 52:1987;345-370.
    • (1987) Psychometrika , vol.52 , pp. 345-370
    • Bozdogan, H.1
  • 2
    • 0001237218 scopus 로고
    • R a maximum likelihood methodology for clusterwise linear regression
    • DeSarbo W.S., Cron W. R A maximum likelihood methodology for clusterwise linear regression. Journal of Classification. 5:1988;249-282.
    • (1988) Journal of Classification , vol.5 , pp. 249-282
    • Desarbo, W.S.1    Cron, W.2
  • 3
    • 55649113136 scopus 로고
    • Preference mapping for product optimisation
    • In T. Naes, & E. Risvik London: Elsevier Applied Science
    • McEwan, J. A. (1995). Preference mapping for product optimisation. In T. Naes, & E. Risvik, Multivariate analysis of data in sensory science (pp. 71-102). London: Elsevier Applied Science.
    • (1995) Multivariate Analysis of Data in Sensory Science , pp. 71-102
    • McEwan, J.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.