Extra Sum-of-Squares F-Test for modeler Objects

Perform an extra sum-of-squares F-test to compare two nested models of class modeler. This test assesses whether the additional parameters in the full model significantly improve the fit compared to the reduced model.

Usage

# S3 method for class 'modeler'
anova(reduced_model, full_model = NULL, ...)

Arguments

reduced_model: An object of class modeler representing the reduced model with fewer parameters.
full_model: An optional object of class modeler representing the full model with more parameters.
...: Additional parameters for future functionality.

Value

A tibble containing columns with the F-statistic and corresponding p-values, indicating whether the full model provides a significantly better fit than the reduced model.

Author

Johan Aparicio [aut]

Examples

library(flexFitR)
dt <- data.frame(X = 1:6, Y = c(12, 16, 44, 50, 95, 100))
mo_1 <- modeler(dt, X, Y, fn = "fn_lin", param = c(m = 10, b = -5))
#> Loading required package: foreach
#> Loading required package: future
plot(mo_1)

mo_2 <- modeler(dt, X, Y, fn = "fn_quad", param = c(a = 1, b = 10, c = 5))
plot(mo_2)

anova(mo_1, mo_2)
#> # A tibble: 1 × 9
#>     uid RSS_reduced RSS_full     n   df1   df2     F `Pr(>F)` .    
#>   <dbl>       <dbl>    <dbl> <int> <int> <int> <dbl>    <dbl> <fct>
#> 1     1        449.     385.     6     1     3 0.494    0.533 ns