FitMultipleDynamicGrowth {biogrowth} | R Documentation |
The class FitMultipleDynamicGrowth has been superseded by the top-level class GlobalGrowthFit, which provides a unified approach for growth modelling.
Still, it is still returned if the superseded fit_multiple_growth()
is called.
It is a subclass of list with the items:
fit_results: the object returned by modFit
.
best_prediction: a list with the models predictions for each condition.
data: a list with the data used for the fit.
starting: starting values for model fitting
known: parameter values set as known.
sec_models: a named vector with the secondary model for each environmental factor.
## S3 method for class 'FitMultipleDynamicGrowth'
print(x, ...)
## S3 method for class 'FitMultipleDynamicGrowth'
plot(
x,
y = NULL,
...,
add_factor = NULL,
ylims = NULL,
label_x = "time",
label_y1 = "logN",
label_y2 = add_factor,
line_col = "black",
line_size = 1,
line_type = "solid",
line_col2 = "black",
line_size2 = 1,
line_type2 = "dashed",
point_size = 3,
point_shape = 16,
subplot_labels = "AUTO"
)
## S3 method for class 'FitMultipleDynamicGrowth'
summary(object, ...)
## S3 method for class 'FitMultipleDynamicGrowth'
residuals(object, ...)
## S3 method for class 'FitMultipleDynamicGrowth'
coef(object, ...)
## S3 method for class 'FitMultipleDynamicGrowth'
vcov(object, ...)
## S3 method for class 'FitMultipleDynamicGrowth'
deviance(object, ...)
## S3 method for class 'FitMultipleDynamicGrowth'
fitted(object, ...)
## S3 method for class 'FitMultipleDynamicGrowth'
predict(object, env_conditions, times = NULL, ...)
## S3 method for class 'FitMultipleDynamicGrowth'
logLik(object, ...)
## S3 method for class 'FitMultipleDynamicGrowth'
AIC(object, ..., k = 2)
x |
an instance of FitMultipleDynamicGrowth. |
... |
ignored |
y |
ignored |
add_factor |
whether to plot also one environmental factor.
If |
ylims |
A two dimensional vector with the limits of the primary y-axis. |
label_x |
label of the x-axis |
label_y1 |
Label of the primary y-axis. |
label_y2 |
Label of the secondary y-axis. |
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: |
line_col2 |
Same as lin_col, but for the environmental factor. |
line_size2 |
Same as line_size, but for the environmental factor. |
line_type2 |
Same as lin_type, but for the environmental factor. |
point_size |
Size of the data points |
point_shape |
shape of the data points |
subplot_labels |
labels of the subplots according to |
object |
an instance of FitMultipleDynamicGrowth |
env_conditions |
a tibble describing the environmental conditions (as
in |
times |
A numeric vector with the time points for the simulations. |
k |
penalty for the parameters (k=2 by default) |
print(FitMultipleDynamicGrowth)
: print of the model
plot(FitMultipleDynamicGrowth)
: comparison between the fitted model and
the experimental data.
summary(FitMultipleDynamicGrowth)
: statistical summary of the fit.
residuals(FitMultipleDynamicGrowth)
: calculates the model residuals. Returns a
tibble with 4 columns: time (storage time), logN (observed count),
exp (name of the experiment) and res (residual).
coef(FitMultipleDynamicGrowth)
: vector of fitted parameters.
vcov(FitMultipleDynamicGrowth)
: (unscaled) variance-covariance matrix,
estimated as 1/(0.5*Hessian).
deviance(FitMultipleDynamicGrowth)
: deviance of the model.
fitted(FitMultipleDynamicGrowth)
: fitted values. They are returned as a
tibble with 3 columns: time (storage time), exp (experiment
identifier) and fitted (fitted value).
predict(FitMultipleDynamicGrowth)
: vector of model predictions
logLik(FitMultipleDynamicGrowth)
: loglikelihood of the model
AIC(FitMultipleDynamicGrowth)
: Akaike Information Criterion