NDLI: Randomly Truncated Nonlinear Mixed-Effects Models

Content Provider	Springer Nature Link
Author	Paraíba, Carolina Costa Mota Diniz, Carlos Alberto Ribeiro
Copyright Year	2016
Abstract	A class of truncated nonlinear mixed-effects models is constructed by assuming that the variable of interest follows a truncated distribution parametrized by a location and a scale parameter. The location parameter of the responses is associated with a nonlinear continuous function of covariates and unknown parameters, and with unobserved random effects. We also assume the scale parameter of the responses to be characterized by a known continuous function of covariates and unknown parameters. Maximum likelihood estimator of the parameters is obtained by direct maximization of the log-likelihood function via an iterative procedure, and diagnostic analysis tools are considered to check for model adequacy. A data set consisting of observations on soil-water retention from a soil profile from the Buriti Vermelho River Basin database is analyzed using the proposed methodology.
Starting Page	295
Ending Page	313
Page Count	19
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	21
Issue Number	2
e-ISSN	15372693
Language	English
Publisher	Springer US
Publisher Date	2016-02-16
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Iterative maximum likelihood Diagnostic analysis Soil-water retention Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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