FitMultipleDynamicGrowth {biogrowth}  R Documentation 
FitMultipleDynamicGrowth class
Description
The class FitMultipleDynamicGrowth has been superseded by the toplevel class GlobalGrowthFit, which provides a unified approach for growth modelling.
Still, it is still returned if the superseded fit_multiple_growth()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.
Usage
## 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)
Arguments
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 yaxis. 
label_x 
label of the xaxis 
label_y1 
Label of the primary yaxis. 
label_y2 
Label of the secondary yaxis. 
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 (16) 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) 
Methods (by generic)

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) variancecovariance 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