fit.weib.models: fit.weib.models
In ForestPlots/BiomasaFP: BiomasaFP: Functions for analysing data downloaded from ForestPlots.net
View source: R/fit_weib_models.r
fit.weib.models R Documentation
fit.weib.models
Description
Function to fit Weibull and log-log height-diameter models.
Usage
fit.weib.models(x, thresh = 20, weib.only = FALSE)
Arguments
x
Dataframe with columns names Height (consisting of measured heights), Diameter (measured diameters) and WD (wood density). These will be present if an object return by mergefp is used.
thresh
Minimum number of height observations needed to attempt to fit models
weib.only
Logical. Should the search for the best model be constrained to Weibull models. If TRUE, log-log models are only selected when neither Weibull models converge. Default is FALSE.
Value
Dataframe with estimated parameters, number of height measurments used to fit the models and the error at estimating AGB compared to AGB estimates using observed heights (in units of Mg per tree). Parameters of the 'best' model (i.e. lowest AGB prediction error) are also given.
Author(s)
Martin Sullivan
ForestPlots/BiomasaFP documentation built on April 28, 2023, 8:26 a.m.
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View source: R/fit_weib_models.r
| fit.weib.models | R Documentation |
fit.weib.models
Description
Function to fit Weibull and log-log height-diameter models.
Usage
fit.weib.models(x, thresh = 20, weib.only = FALSE)
Arguments
x |
Dataframe with columns names Height (consisting of measured heights), Diameter (measured diameters) and WD (wood density). These will be present if an object return by |
thresh |
Minimum number of height observations needed to attempt to fit models |
weib.only |
Logical. Should the search for the best model be constrained to Weibull models. If TRUE, log-log models are only selected when neither Weibull models converge. Default is FALSE. |
Value
Dataframe with estimated parameters, number of height measurments used to fit the models and the error at estimating AGB compared to AGB estimates using observed heights (in units of Mg per tree). Parameters of the 'best' model (i.e. lowest AGB prediction error) are also given.
Author(s)
Martin Sullivan
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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