Predictive posterior distributions from a Bayesian version of a slash pine yield model

被引：1

作者：

Green, EJ ^{[1
]}

Strawderman, WE ^{[1
]}

机构：

[1] RUTGERS STATE UNIV,DEPT STAT,NEW BRUNSWICK,NJ 08903

来源：

FOREST SCIENCE | 1996年 / 42卷 / 04期

关键词：

Gibbs sampler; Weibull distribution;

D O I：

暂无

中图分类号：

S7 [林业];

学科分类号：

0829 ; 0907 ;

摘要：

We formulate a traditional slash pine diameter distribution yield model in a Bayesian framework. We attempt to introduce as few new assumptions as possible. We generate predictive posterior samples for a number of stand Variables using the Gibbs sampler. The means of the samples agree well with the predictions from the published model. In addition, our model delivers distributions of outcomes, from which it is easy to establish measures of uncertainty, e.g., Bayesian credible regions.

引用

页码：456 / 464

页数：9

共 49 条

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