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biogrowth (version 1.0.6)

FitSecondaryGrowth: FitSecondaryGrowth class

Description

The FitSecondaryGrowth class contains a model fitted to a set of growth rates gathered under a variety of static conditions. Its constructor is fit_secondary_growth().

It is a subclass of list with the items:

  • fit_results: object returned by FME::modFit().

  • secondary_model: secondary model fitted to the data.

  • mu_opt_fit: estimated growth rate under optimum conditions.

  • data: data used for the fit.

  • transformation: type of transformation of mu for the fit.

Usage

# S3 method for FitSecondaryGrowth
print(x, ...)
# S3 method for FitSecondaryGrowth
plot(x, y = NULL, ..., which = 1, add_trend = FALSE, add_segment = FALSE)
# S3 method for FitSecondaryGrowth
summary(object, ...)
# S3 method for FitSecondaryGrowth
residuals(object, ...)
# S3 method for FitSecondaryGrowth
coef(object, ...)
# S3 method for FitSecondaryGrowth
vcov(object, ...)
# S3 method for FitSecondaryGrowth
deviance(object, ...)
# S3 method for FitSecondaryGrowth
fitted(object, ...)
# S3 method for FitSecondaryGrowth
predict(object, newdata = NULL, ...)
# S3 method for FitSecondaryGrowth
logLik(object, ...)
# S3 method for FitSecondaryGrowth
AIC(object, ..., k = 2)

Arguments

x

An instance of FitSecondaryGrowth.

...

ignored

y

ignored.

which

A numeric with the type of plot. 1 for obs versus predicted (default), 2 for gamma curve

add_trend

Whether to add a trend line (only for which=2)

add_segment

Whether to join the observed and fitted points (only for which=2)

object

an instance of FitSecondaryGrowth

newdata

A tibble describing the environmental conditions as in fit_secondary_growth(). If NULL, it uses the same conditions as for model fitting (default).

k

penalty for the parameters (k=2 by default)

Methods (by generic)

  • print(FitSecondaryGrowth): print of the model

  • plot(FitSecondaryGrowth): plots to evaluate the goodness of the fit.

  • summary(FitSecondaryGrowth): statistical summary of the fit.

  • residuals(FitSecondaryGrowth): vector of model residuals.

  • coef(FitSecondaryGrowth): vector of fitted model parameters.

  • vcov(FitSecondaryGrowth): variance-covariance matrix of the model, estimated as 1/(0.5*Hessian)

  • deviance(FitSecondaryGrowth): deviance of the model.

  • fitted(FitSecondaryGrowth): vector of fitted values.

    The fitted values are returned in the same scale as the one used for the fitting (sqrt, log or none).

  • predict(FitSecondaryGrowth): vector of model predictions.

  • logLik(FitSecondaryGrowth): loglikelihood of the model

  • AIC(FitSecondaryGrowth): Akaike Information Criterion