est_clutter {forestmangr} | R Documentation |
Estimate future and present basal area, volume, TCA, CMI and MMI values of the Clutter Growth and Yield Model
Description
This function estimates the present the present value of basal area for each class using either the class mean, or a linear quadratic model, and then uses it's value to calculate the basal area from Clutter's growth and yield model.
Usage
est_clutter(
df,
age,
basal_area,
site,
category,
coeffs,
method = "average",
annual_increment = FALSE,
gray_scale = TRUE,
output = "table"
)
Arguments
df |
A data frame. |
age |
A numeric vector with the desired age range to be used in the estimation, or a Quoted name for the age variable. |
basal_area |
Quoted name for the basal area variable. |
site |
Quoted name for the average site variable. |
category |
Quoted name for the category variable. |
coeffs |
Numeric vector or a data frame with the fitted values of Clutter's growth and yield model. It must be a named vector, with b0,b1,b2,b3,a0 and a1 as names. a1 is not obligatory. |
method |
Method used for estimating the present basal area of each class. It can either be the class' average basal area |
annual_increment |
If |
gray_scale |
If |
output |
Type of output the function should return. This can either be |
Value
A data frame, a ggplot object or a list, according to output.
Author(s)
Sollano Rabelo Braga sollanorb@gmail.com
See Also
other sampling functions:
fit_clutter
for fitting the clutter growth and Yield model, and
classify_site
for classifying data according to site.
Examples
library(forestmangr)
data("exfm17")
head(exfm17)
clutter <- fit_clutter(exfm17, "age", "DH", "B", "V", "S", "plot")
clutter
# Classify data into 3 classes:
ex_class <- classify_site(exfm17, "S", 3, "plot")
head(ex_class ,15)
# Estimate basal area using the average basal area as the initial basal area,
# volume, Mean Monthly Increment (MMI) and Current Monthly Increment (CMI)
# values using Clutter's model:
est_clutter(ex_class,20:125, "B","S","category_",clutter,"average")
# For a more detailed output, including a plot, use output="full":
est_clutter(ex_class,20:125, "B","S","category_",clutter, output="full")
# Estimate basal area using an estimated basal area as the initial basal area:
est_clutter(ex_class,20:125,"B","S","category_",clutter,"model")
# age can be a variable:
est_clutter(ex_class,"age","B","S","category_", clutter,"model")