| guide_curve | R Documentation | 
Get the guide curve for growth and yield analysis of inventory data using the factor method, and different statistical models.
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"
)
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   | 
model | 
 model used to fit dh as a function of age. The models available are   | 
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:   | 
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:   | 
round_classes | 
 If   | 
font | 
 Type of font used in the plot. Default:   | 
gray_scale | 
 If   | 
output | 
 Type of output the function should return. This can either be   | 
A data frame, a ggplot object, or a list, varying according to the "output" argument.
Sollano Rabelo Braga sollanorb@gmail.com
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)
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