tidy.Mclust {broom} | R Documentation |
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 cross 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 class 'Mclust' tidy(x, ...)
x |
An |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
A tibble::tibble with one row per component:
component |
Cluster id as a factor. For a model |
size |
Number of observations assigned to component |
proportion |
The mixing proportion of each component |
variance |
In case of one-dimensional and spherical models, the variance for each component, omitted otherwise. NA for noise component |
mean |
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 |
Other mclust tidiers:
augment.Mclust()
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) ) %>% select(-num_points, -cluster) %>% tidyr::unnest(x1, x2) m <- mclust::Mclust(points) tidy(m) augment(m, points) glance(m)