Performs Analysis of Variance on a 'tidyFit' R6 class. The function can be used with regress or classify.
Arguments
- self
a 'tidyFit' R6 class.
- data
a data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr).
Details
Hyperparameters:
None. Cross validation not applicable.
Important method arguments (passed to m)
The function provides a wrapper for stats::anova. See ?anova for more details.
First a glm model is fitted which is passed to anova.
Examples
# Load data
data <- tidyfit::Factor_Industry_Returns
# Stand-alone function
fit <- m("anova", Return ~ `Mkt-RF` + HML + SMB, data)
fit
#> # A tibble: 1 × 5
#> estimator_fct `size (MB)` grid_id model_object settings
#> <chr> <dbl> <chr> <list> <list>
#> 1 stats::anova 0.00186 #0010000 <tidyFit> <tibble [1 × 1]>
# Within 'regress' function
fit <- regress(data, Return ~ ., m("anova"), .mask = c("Date", "Industry"))
tidyr::unnest(coef(fit), model_info)
#> # A tibble: 7 × 6
#> # Groups: model [1]
#> model term df deviance df.residual residual.deviance
#> <chr> <chr> <int> <dbl> <int> <dbl>
#> 1 anova NULL NA NA 7079 198728.
#> 2 anova Mkt-RF 1 122219. 7078 76509.
#> 3 anova SMB 1 19.7 7077 76489.
#> 4 anova HML 1 896. 7076 75593.
#> 5 anova RMW 1 612. 7075 74981.
#> 6 anova CMA 1 172. 7074 74809.
#> 7 anova RF 1 505. 7073 74303.