guide_curve {forestmangr}R Documentation

Get the guide curve plot for growth and yield analysis of inventory data

Description

Get the guide curve for growth and yield analysis of inventory data using the factor method, and different statistical models.

Usage

guide_curve(
  df,
  dh,
  age,
  age_index,
  n_class = 4,
  model = "Schumacher",
  start_chap = c(b0 = 23, b1 = 0.03, b2 = 1.3),
  start_bailey = c(b0 = 3, b1 = -130, b2 = 1.5),
  round_classes = FALSE,
  font = "serif",
  gray_scale = TRUE,
  output = "plot"
)

Arguments

df

A data frame.

dh

Quoted name for the dominant height variable.

age

Quoted name for the age variable.

age_index

Numeric value for the age index.

n_class

Numeric value for the number of classes used to divide the data. Default 4.

model

model used to fit dh as a function of age. The models available are "Schumacher", "Curtis", "Chapman-Richards" and "Bailey-Clutter". Default: "Schumacher".

start_chap

Numeric vector with the start values for the Chapman-Richards model. This must be a named vector, with b0, b1 and b2 as parameter names. Default: c(b0=23, b1=0.03, b2 = 1.3).

start_bailey

Numeric vector with the start values for the Bailey-Clutter model. This must be a named vector, with b0, b1 and b2 as parameter names. Default: c( b0=3, b1=-130, b2 = 1.5).

round_classes

If TRUE, class values will be rounded to the nearest 5. Default TRUE.

font

Type of font used in the plot. Default: "serif".

gray_scale

If TRUE, the plot will be rendered in a gray scale. Default: "TRUE".

output

Type of output the function should return. This can either be "plot", for the guide curve plot, "table", for a data frame with the data used on the guide curve plot, and "full" for a list with 2 ggplot2 objects, one for residual plot and other for plot curves, a lm object for the regression, a data frame with quality of fit variables, the dominant height index, the class table used, and the table used for the guide curve plot. Default "plot".

Value

A data frame, a ggplot object, or a list, varying according to the "output" argument.

Author(s)

Sollano Rabelo Braga sollanorb@gmail.com

Examples

data("exfm14")
head(exfm14)

# To get a guide curve plot for this data, we simply need to input
# dominant height and age variables, age index, and number of classes to be used:
guide_curve(exfm14, "dh", "age", 72, 5)

# if we want to get the table used to get the plot, we can choose the output "table":
guide_curve(exfm14, "dh", "age", 72, 5, output = "table")

# Other models are available for use, such as Curtis, Chapman Richards, and Bailey:
# CR and BC models are non linear, and thus need start values. There are default values,
# but they may fail, depending on the data used, so it's recommended to try start values that
# are ideal for the data used:
guide_curve(exfm14, "dh", "age", 72, 5,
 model = "Chapman-Richards", start_chap = c(b0=23, b1=0.03, b2 = 1.3))

# Or, to get more information on the analysis, such as details on the regression,
# bias, rmse, plot for residuals and more (cpu taxing):
## Not run: 
guide_curve(exfm14, "dh", "age", 72, 5, output = "full")

## End(Not run)

[Package forestmangr version 0.9.6 Index]