Mingliang Wang, Ph.D. - Publications
Affiliations: | 2011 | Graduate School - New Brunswick | Rutgers University, New Brunswick, New Brunswick, NJ, United States |
Area:
Computer Science, Computer EngineeringYear | Citation | Score | |||
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2019 | Fu L, Wang M, Wang Z, Song X, Tang S. Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming International Journal of Biomathematics. 12: 1950040. DOI: 10.1142/S1793524519500402 | 0.304 | |||
2014 | Wang M, Kane MB, Borders BE, Zhao D. Direct Variance-Covariance Modeling as an Alternative to the Traditional Guide Curve Approach for Prediction of Dominant Heights Forest Science. 60: 652-662. DOI: 10.5849/Forsci.13-019 | 0.324 | |||
2014 | Fu L, Wang M, Lei Y, Tang S. Parameter estimation of two-level nonlinear mixed effects models using first order conditional linearization and the EM algorithm Computational Statistics & Data Analysis. 69: 173-183. DOI: 10.1016/J.Csda.2013.05.026 | 0.301 | |||
2010 | Wang M, Upadhyay A, Zhang L. Trivariate distribution modeling of tree diameter, height, and volume. Forest Science. 56: 290-300. DOI: 10.1093/Forestscience/56.3.290 | 0.331 | |||
2008 | Wang M, Rennolls K, Tang S. Bivariate Distribution Modeling of Tree Diameters and Heights: Dependency Modeling Using Copulas Forest Science. 54: 284-293. DOI: 10.1093/Forestscience/54.3.284 | 0.317 | |||
2008 | Wang M, Borders BE, Zhao D. An empirical comparison of two subject-specific approaches to dominant heights modeling: The dummy variable method and the mixed model method Forest Ecology and Management. 255: 2659-2669. DOI: 10.1016/J.Foreco.2008.01.030 | 0.311 | |||
2007 | Wang M, Rennolls K. Bivariate distribution modeling with tree diameter and height data Forest Science. 53: 16-24. DOI: 10.1093/Forestscience/53.1.16 | 0.322 | |||
2005 | Rennolls K, Wang M. A new parameterization of Johnson's SB distribution with application to fitting forest tree diameter data Canadian Journal of Forest Research. 35: 575-579. DOI: 10.1139/X05-006 | 0.317 | |||
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