RECORD
Bayesian Modeling of Forestry Data with R Using Optimization and Simulation Tools
- Title:
- Bayesian Modeling of Forestry Data with R Using Optimization and Simulation Tools
- Creator:
- Khan, Yasmin; Akhtar, Md Tanwir; Shehla, Romana; Khan, A.A.
- Date Created:
- 2015-02
- Description:
- Data generated in forestry biometrics are not normal in statistical sense as they rarely follow the normal regression model. Hence, there is a need to develop models and methods in forest biometric applications for nonnormal models. Due to generality of Bayesian methods it can be implemented in the situations when Gaussian regression models do not fit the data. Data on diameter at breast height (dbh), which is a very important characteristic in forestry has been fitted to Weibull and gamma models in Bayesian paradigm and comparisons have also been made with its classical counterpart. It may be noted that MCMC simulation tools are used in this study. An attempt has been made to apply Bayesian simulation tools using R software.
- Document Type:
- Research Article
- Subjects:
- UIEF R data modeling forestry biometrics forest statistics regression models Bayesian inference optim sampling importance model comparison forest analytics
- UIEF Unit:
- Flat Creek
- Location:
- UIEF
- Latitude:
- 46.851013
- Longitude:
- -116.724478
- Publisher:
- Journal of Applied Analysis and Computation
- Department:
- Forest, Rangeland, and Fire Sciences
- Source Identifier:
- doi:10.11948/2015004
- Type:
- Text
Source
- Preferred Citation:
- "Bayesian Modeling of Forestry Data with R Using Optimization and Simulation Tools", UIEF Research Exchange, University of Idaho Library Digital Collections, https://www.lib.uidaho.edu/digital/uief/items/uief_0279.html
Rights
- Rights:
- In copyright, educational use permitted.
- Standardized Rights:
- http://rightsstatements.org/vocab/InC-EDU/1.0/