param_4

This matrix contains the posterior distribution of the parameters of Equation 4 of Chave et al. (2014),
obtained in a Bayesian framework with uninformative priors through a Metropolis algorithm.

datasets

internal

AGBmonteCarlo

Contains functions to estimate aboveground biomass/carbon and its uncertainty in tropical forests.
These functions allow to (1) retrieve and to correct taxonomy, (2) estimate wood density and its uncertainty,
(3) construct height-diameter models, (4) manage tree and plot coordinates,
(5) estimate the aboveground biomass/carbon at the stand level with associated uncertainty.
To cite 'BIOMASS', please use citation("BIOMASS").
See more in the article of Réjou-Méchain et al. (2017) <doi:10.1111/2041-210X.12753>.

Dominique Lamonica

BIOMASS

Estimating Aboveground Biomass and Its Uncertainty in Tropical
Forests

Maxime Réjou-Méchain

Guillaume Cornu

Arthur Pere

Ariane Tanguy

Camille Piponiot

Jerome Chave

Bruno Hérault

Ted Feldpausch

Philippe Verley

param_4 function

A data frame with 1001 observations on the following 3 variables.<ul>
<li><code>intercept</code>: Vector of intercept values</li>
<li><code>logagbt</code>: Vector of the model coefficients associated with the product wood density * diameter^2 * height</li>
<li><code>sd</code>: Vector of model residual standard error (RSE) values</li>
</ul>

Format

Posterior distribution of Chave et al.'s 2014 equation 4 parameters — param_4

Posterior distribution of Chave et al.'s 2014 equation 4 parameters

param_4: Posterior distribution of Chave et al.'s 2014 equation 4 parameters

Description

Usage

Arguments

Format

Details

References

Examples