FitCoupledGrowth: FitCoupledGrowth class

Description

The FitCoupledGrowth class contains a Baranyi model fitted to experimental data considering the coupling between the primary and secondary models. Its constructor is fit_coupled_growth().

It is a subclass of list with the items:

fit: object returned by FME::modFit().
mode: fitting approach.
weight: type of weights for the two-steps approach.
logbase_mu: base of the logarithm used for the calculation of mu.
data: data used for the model fitting.

Usage

# S3 method for FitCoupledGrowth
print(x, ...)
# S3 method for FitCoupledGrowth
coef(object, ...)
# S3 method for FitCoupledGrowth
summary(object, ...)
# S3 method for FitCoupledGrowth
predict(object, newdata = NULL, ...)
# S3 method for FitCoupledGrowth
residuals(object, ...)
# S3 method for FitCoupledGrowth
vcov(object, ...)
# S3 method for FitCoupledGrowth
deviance(object, ...)
# S3 method for FitCoupledGrowth
fitted(object, ...)
# S3 method for FitCoupledGrowth
logLik(object, ...)
# S3 method for FitCoupledGrowth
AIC(object, ..., k = 2)
# S3 method for FitCoupledGrowth
plot(
  x,
  y = NULL,
  ...,
  line_col = "black",
  line_size = 1,
  line_type = 1,
  point_col = "black",
  point_size = 3,
  point_shape = 16,
  label_y = NULL,
  label_x = NULL
)
# S3 method for FitCoupledGrowth
predictMCMC_coupled(model, niter, newdata = NULL, includecorr = TRUE)

Arguments

x: The object of class FitCoupledGrowth to plot.
...: ignored.
object: an instance of FitCoupledGrowth
newdata: a data.frame (or tibble) describing experimental conditions. If null, the ones used for the fitting are used (default).
k: penalty for the parameters (k=2 by default)
y: ignored
line_col: colour of the line
line_size: size of the line
line_type: type of the line
point_col: colour of the points
point_size: size of the points
point_shape: shape of the point
label_y: label for the y-axis. By default, NULL (default value depending on the mode)
label_x: label for the x-axis. By default, NULL (default value depending on the mode)
model: an instance of FitCoupledGrowth
niter: Number of MCMC iterations
includecorr: whether to include parameter correlation (TRUE by default)

Methods (by generic)

print(FitCoupledGrowth): print of the model
coef(FitCoupledGrowth): vector of fitted model parameters.
summary(FitCoupledGrowth): statistical summary of the fit.
predict(FitCoupledGrowth): vector of model predictions.
residuals(FitCoupledGrowth): vector of model residuals.
vcov(FitCoupledGrowth): variance-covariance matrix of the model, estimated as 1/(0.5*Hessian) for regression
deviance(FitCoupledGrowth): deviance of the model.
fitted(FitCoupledGrowth): vector of fitted values.
logLik(FitCoupledGrowth): loglikelihood of the model
AIC(FitCoupledGrowth): Akaike Information Criterion
plot(FitCoupledGrowth): compares the fitted model against the data.
predictMCMC_coupled(FitCoupledGrowth): prediction including parameter uncertainty