Show differences between two models

Show differences between two MixAR models in a way that enables quick comparison between them. This is a generic function, package mixAR defines methods for MixAR models.

Usage

show_diff(model1, model2)

Arguments

model1,model2

the MixAR models to be compared.

Details

show_diff() is a generic function with dispatch on both arguments.

show_diff() prints the differences between two models in convenient form for comparison. The methods for MixAR models allow to see differences between similar models at a glance.

Value

The function is called for the side effect of printing the differences between the two models and has no useful return value.

Author

Georgi N. Boshnakov

Methods

signature(model1 = "MixAR", model2 = "MixAR")

signature(model1 = "MixARGaussian", model2 = "MixARgen")

signature(model1 = "MixARgen", model2 = "MixARGaussian")

signature(model1 = "MixARgen", model2 = "MixARgen")

Examples

## the examples reveal that the models below
##        differ only in the noise distributions
show_diff(exampleModels$WL_Ct_3, exampleModels$WL_Bt_1)
#>        prob shift scale order ar_1 ar_2 ar_3
#> Comp_1   0    0     0     2     0    0      
#> Comp_2   0    0     0     1     0           
#> Comp_3   0    0     0     3     0    0    0 
#> 
#> Distributions of the error components:
#> 
#> 	Model 1
#> 	 All components: Standard normal distribution
#> 
#> 	Model 2
#> 	Component 1: Student t with 4 df
#> 	Component 2: Student t with 6 df
#> 	Component 3: Student t with 10 df
show_diff(exampleModels$WL_Bt_1, exampleModels$WL_Ct_3)
#>        prob shift scale order ar_1 ar_2 ar_3
#> Comp_1   0    0     0     2     0    0      
#> Comp_2   0    0     0     1     0           
#> Comp_3   0    0     0     3     0    0    0 
#> 
#> Distributions of the error components:
#> 
#> 	Model 1
#> 	Component 1: Student t with 4 df
#> 	Component 2: Student t with 6 df
#> 	Component 3: Student t with 10 df
#> 
#> 	Model 2
#> 	 All components: Standard normal distribution
show_diff(exampleModels$WL_Ct_2, exampleModels$WL_Bt_3)
#>        prob shift scale order ar_1 ar_2 ar_3
#> Comp_1   0    0     0     2     0    0      
#> Comp_2   0    0     0     1     0           
#> Comp_3   0    0     0     3     0    0    0 
#> 
#> Distributions of the error components:
#> 
#> 	Model 1:
#> 	Component 1: Student t with 4 df
#> 	Component 2: Student t with 7 df
#> 	Component 3: Standard normal distribution
#> 
#> 	Model 2:
#> 	Component 1: Student t with 4 df
#> 	Component 2: Student t with 4 df
#> 	Component 3: Student t with 10 df