
Review SOM map support before fitting a SOM + Mclust model
Source:R/SOMMapSupport.R
SOMMapSupport.RdCalculates the competing codebook-node support and participant occupancy constraints for a planned SOM + Mclust search. Mclust is fit to SOM codebook vectors, so its effective sample size is the number of nodes; participant count instead limits how sparse a map should become.
Usage
SOMMapSupport(
n,
p,
k_range,
models,
min_nodes_per_parameter = 3,
min_participants_per_node = 10
)Arguments
- n
Number of complete training participants.
- p
Number of post-preprocessing clustering variables entering Mclust.
- k_range
Requested profile counts.
- models
TidyLPA Mclust model IDs (1, 2, 3, or 6).
- min_nodes_per_parameter
Target codebook nodes per estimated mixture parameter. Default
3.- min_participants_per_node
Target complete training participants per SOM node. Default
10; this is an engineering map-health target, not a universal statistical threshold.
Value
A tibble with one row per model/k candidate and common map-sizing
diagnostics. SupportStatus is "supported", "under-supported", or
"over-parameterized" at the recommended automatic map size.
Examples
SOMMapSupport(n = 4330, p = 11, k_range = 2:8, models = 1:3)
#> # A tibble: 21 × 18
#> Model Classes MixtureParameters ParameterFloorSide MixtureNodes
#> <int> <int> <int> <dbl> <int>
#> 1 1 2 34 11 400
#> 2 1 3 46 12 400
#> 3 1 4 58 14 400
#> 4 1 5 70 15 400
#> 5 1 6 82 16 400
#> 6 1 7 94 17 400
#> 7 1 8 106 18 400
#> 8 2 2 45 12 400
#> 9 2 3 68 15 400
#> 10 2 4 91 17 400
#> # ℹ 11 more rows
#> # ℹ 13 more variables: ParticipantsPerNode <dbl>, OccupancyCompliant <lgl>,
#> # NodesPerParameter <dbl>, Overparameterized <lgl>, SupportStatus <chr>,
#> # SOMSide <int>, BaseSide <int>, FloorSide <int>, OccupancyCeilingSide <int>,
#> # RecommendedSide <int>, BindingConstraint <chr>, MinNodesPerParameter <dbl>,
#> # MinParticipantsPerNode <dbl>