FitSecondaryGrowth: FitSecondaryGrowth class

In biogrowth: Modelling of Population Growth

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 class 'FitSecondaryGrowth'
print(x, ...)

## S3 method for class 'FitSecondaryGrowth'
plot(x, y = NULL, ..., which = 1, add_trend = FALSE, add_segment = FALSE)

## S3 method for class 'FitSecondaryGrowth'
summary(object, ...)

## S3 method for class 'FitSecondaryGrowth'
residuals(object, ...)

## S3 method for class 'FitSecondaryGrowth'
coef(object, ...)

## S3 method for class 'FitSecondaryGrowth'
vcov(object, ...)

## S3 method for class 'FitSecondaryGrowth'
deviance(object, ...)

## S3 method for class 'FitSecondaryGrowth'
fitted(object, ...)

## S3 method for class 'FitSecondaryGrowth'
predict(object, newdata = NULL, ...)

## S3 method for class 'FitSecondaryGrowth'
logLik(object, ...)

## S3 method for class '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

biogrowth documentation built on April 13, 2025, 5:12 p.m.