Cache list, containing the last fitted model, data frame and formula

A list, will be used if cache = TRUE while calling the fit method.

Examples

# Instantiate
x <- rand_uniform()
e <- rand_normal()
test <- vi_model(prm = list(x = x, e = e),
                 prm_type = list(x = "r", e = "r"),
                 formula = y ~ 1 + x + x^2 + e,
                 null_formula = y ~ x,
                 alt_formula = y ~ x + I(x^2))

# Turn on cache
test$fit(test$gen(10), cache = TRUE)
#> 
#> Call:
#> stats::lm(formula = y ~ x, data = test$gen(10))
#> 
#> Coefficients:
#> (Intercept)            x  
#>      0.5371       2.4550  
#> 

test$..cache..
#> $dat
#>             y          x           e     .resid   .fitted
#> 1  2.70041295 0.89184237  0.01318775 -0.4861032 3.1865161
#> 2  0.36658615 0.53451153 -1.45362796 -1.7961332 2.1627193
#> 3  0.14277243 0.01523344 -0.87269307 -0.5321513 0.6749237
#> 4  3.93123433 0.60936551  1.95054251  1.5540492 2.3771852
#> 5  3.59532086 0.98478629  0.64073053  0.1425090 3.4528119
#> 6  4.14476037 0.64215488  2.09024261  1.6736296 2.4711307
#> 7  1.14252524 0.63887879 -0.90451966 -1.3192191 2.4617443
#> 8  1.88783385 0.09722767  0.78115296  0.9779866 0.9098473
#> 9  1.72102519 0.13497229  0.56783538  0.7030349 1.0179902
#> 10 0.04940525 0.11717814 -1.08150361 -0.9176026 0.9670078
#> 
#> $formula
#> y ~ x
#> 
#> $mod
#> 
#> Call:
#> stats::lm(formula = y ~ x, data = test$gen(10))
#> 
#> Coefficients:
#> (Intercept)            x  
#>      0.5371       2.4550  
#> 
#>