GrowthComparison {biogrowth}

GrowthComparison class

Description

The GrowthComparison class contains several functions for model comparison and model selection of growth models. It should not be instanced directly. Instead, it should be constructed using compare_growth_fits().

It includes two type of tools for model selection and comparison: statistical indexes and visual analyses. Please check the sections below for details.

Note that all these tools use the names defined in compare_growth_fits(), so we recommend passing a named list to that function.

Usage

## S3 method for class 'GrowthComparison'
plot(x, y, ..., type = 1, add_trend = TRUE)

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

## S3 method for class 'GrowthComparison'
print(x, ...)

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

Arguments

x

an instance of GrowthComparison

y

ignored

...

ignored

type

if type==1, the plot compares the model predictions. If type ==2, the plot compares the parameter estimates. If type==3, the plot shows the residuals

add_trend

should a trend line of the residuals be added for type==3? TRUE by default

object

an instance of GrowthComparison

Methods (by generic)

• plot(GrowthComparison): illustrations comparing the fitted models

• coef(GrowthComparison): table of parameter estimates

• print(GrowthComparison): print of the model comparison

• summary(GrowthComparison): summary table for the comparison

Statistical indexes

GrowthComparison implements two S3 methods to obtain numerical values to facilitate model comparison and selection.

• the coef method returns a tibble with the values of the parameter estimates and their corresponding standard errors for each model.

• the summary returns a tibble with the AIC, number of degrees of freedom, mean error and root mean squared error for each model.

Visual analyses

The S3 plot method can generate three types of plots:

• when type = 1, the plot compares the fitted growth curves against the experimental data used to fit the model.

• when type = 2, the plot compares the parameter estimates using error bars, where the limits of the error bars are the expected value +/- one standard error. In case one model does not have some model parameter (i.e. either because it is not defined or because it was fixed), the parameter is not included in the plot.

• when type=3, the plot shows the tendency of the residuals for each model. This plot can be used to detect deviations from independence.