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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