FitDynamicGrowth: FitDynamicGrowth class

FitDynamicGrowthR Documentation

FitDynamicGrowth class

Description

[Superseded]

The class FitDynamicGrowth has been superseded by the top-level class GrowthFit, which provides a unified approach for growth modelling.

Still, it is still returned if the superseded fit_dynamic_growth() is called.

It is a subclass of list with the items:

  • fit_results: the object returned by modFit.

  • best_prediction: the model prediction for the fitted parameters.

  • env_conditions: environmental conditions for the fit.

  • data: 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 'FitDynamicGrowth'
print(x, ...)

## S3 method for class 'FitDynamicGrowth'
plot(
  x,
  y = NULL,
  ...,
  add_factor = NULL,
  ylims = NULL,
  label_y1 = "logN",
  label_y2 = add_factor,
  line_col = "black",
  line_size = 1,
  line_type = 1,
  point_col = "black",
  point_size = 3,
  point_shape = 16,
  line_col2 = "black",
  line_size2 = 1,
  line_type2 = "dashed"
)

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

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

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

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

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

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

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

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

## S3 method for class 'FitDynamicGrowth'
AIC(object, ..., k = 2)

Arguments

x

The object of class FitDynamicGrowth to plot.

...

ignored

y

ignored

add_factor

whether to plot also one environmental factor. If NULL (default), no environmental factor is plotted. If set to one character string that matches one entry of x$env_conditions, that condition is plotted in the secondary axis

ylims

A two dimensional vector with the limits of the primary y-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: geom_line()

line_size

Aesthetic parameter to change the thickness of the line geom in the plot, see: geom_line()

line_type

Aesthetic parameter to change the type of the line geom in the plot, takes numbers (1-6) or strings ("solid") see: geom_line()

point_col

Aesthetic parameter to change the colour of the point geom, see: geom_point()

point_size

Aesthetic parameter to change the size of the point geom, see: geom_point()

point_shape

Aesthetic parameter to change the shape of the point geom, see: geom_point()

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.

object

an instance of FitDynamicGrowth

times

A numeric vector with the time points for the simulations. NULL by default (using the same time points as those for the simulation).

newdata

a tibble describing the environmental conditions (as env_conditions) in predict_dynamic_growth(). If NULL (default), uses the same conditions as those for fitting.

k

penalty for the parameters (k=2 by default)

Functions

  • print.FitDynamicGrowth: comparison between the fitted model and the data.

  • plot.FitDynamicGrowth: comparison between the fitted model and the data.

  • summary.FitDynamicGrowth: statistical summary of the fit.

  • residuals.FitDynamicGrowth: residuals of the model.

  • coef.FitDynamicGrowth: vector of fitted parameters.

  • vcov.FitDynamicGrowth: (unscaled) variance-covariance matrix of the model, calculated as 1/(0.5*Hessian)

  • deviance.FitDynamicGrowth: deviance of the model.

  • fitted.FitDynamicGrowth: fitted values.

  • predict.FitDynamicGrowth: model predictions.

  • logLik.FitDynamicGrowth: loglikelihood of the model

  • AIC.FitDynamicGrowth: Akaike Information Criterion


biogrowth documentation built on July 20, 2022, 1:09 a.m.