Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
# S3 method for Mclust tidy(x, ...)
x | An |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
Other mclust tidiers:
augment.Mclust()
A tibble::tibble()
with columns:
The mixing proportion of each component
Number of points assigned to cluster.
The mean for each component. In case of 2+ dimensional models, a column with the mean is added for each dimension. NA for noise component
In case of one-dimensional and spherical models, the variance for each component, omitted otherwise. NA for noise component
Cluster id as a factor.
if (requireNamespace("mclust", quietly = TRUE)) { library(dplyr) library(mclust) set.seed(27) centers <- tibble::tibble( cluster = factor(1:3), num_points = c(100, 150, 50), # number points in each cluster x1 = c(5, 0, -3), # x1 coordinate of cluster center x2 = c(-1, 1, -2) # x2 coordinate of cluster center ) points <- centers %>% mutate( x1 = purrr::map2(num_points, x1, rnorm), x2 = purrr::map2(num_points, x2, rnorm) ) %>% dplyr::select(-num_points, -cluster) %>% tidyr::unnest(c(x1, x2)) m <- mclust::Mclust(points) tidy(m) augment(m, points) glance(m) } #> # A tibble: 1 × 7 #> model G BIC logLik df hypvol nobs #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <int> #> 1 EII 3 -2402. -1175. 9 NA 300