StochasticGrowth {biogrowth} | R Documentation |
The class StochasticGrowth has been deprecated by class GrowthUncertainty, which provides less misleading name.
Still, it is still returned if the deprecated predict_stochastic_growth()
is called.
The StochasticGrowth
class contains the results of a growth prediction
under isothermal conditions considering parameter unceratinty. Its constructor
is predict_stochastic_growth()
.
It is a subclass of list with the items:
sample: parameter sample used for the calculations.
simulations: growth curves predicted for each parameter.
quantiles: limits of the credible intervals (5%, 10%, 50%, 90%, 95%) for each time point.
model: Model used for the calculations.
mus: Mean parameter values used for the simulations.
sigma: Variance-covariance matrix used for the simulations.
## S3 method for class 'StochasticGrowth'
print(x, ...)
## S3 method for class 'StochasticGrowth'
plot(
x,
y = NULL,
...,
line_col = "black",
line_size = 0.5,
line_type = "solid",
ribbon80_fill = "grey",
ribbon90_fill = "grey",
alpha80 = 0.5,
alpha90 = 0.4
)
x |
The object of class |
... |
ignored. |
y |
ignored |
line_col |
Aesthetic parameter to change the colour of the line geom in the plot, see: |
line_size |
Aesthetic parameter to change the thickness of the line geom in the plot, see: |
line_type |
Aesthetic parameter to change the type of the line geom in the plot, takes numbers (1-6) or strings ("solid") see: |
ribbon80_fill |
fill colour for the space between the 10th and 90th quantile, see: |
ribbon90_fill |
fill colour for the space between the 5th and 95th quantile, see: |
alpha80 |
transparency of the ribbon aesthetic for the space between the 10th and 90th quantile. Takes a value between 0 (fully transparant) and 1 (fully opaque) |
alpha90 |
transparency of the ribbon aesthetic for the space between the 5th and 95th quantile. Takes a value between 0 (fully transparant) and 1 (fully opaque). |
FitIsoGrowth class
print(StochasticGrowth)
: print of the model
plot(StochasticGrowth)
: Growth prediction (prediction band) considering
parameter uncertainty.