期刊名称：International Journal of Statistics and Probability
印刷版ISSN：1927-7032
电子版ISSN：1927-7040
出版年度：2013
卷号：2
期号：1
页码：101
DOI：10.5539/ijsp.v2n1p101
出版社：Canadian Center of Science and Education
摘要：We propose a flexible linear calibration model with errors from RS (Ramberg \& Schmeiser, 1974) generalized lambda distribution ($G\lambda D$). We demonstrate the derivation of the maximum likelihood estimates of RS $G\lambda D$ parameters and examine the estimation performance using a simulation study for sample sizes ranging from 30 to 200. The use of RS $G\lambda D$ calibration model not only provides statistical modeller with a richer range of distributional shapes, but can also provide more precise parameter estimates compared to the standard Normal calibration model or skewed Normal calibration model proposed by Figueiredoa, Bolfarinea, Sandovala and Limab (2010).
