Alternative edge weight functions for network-based item selection

These functions provide different approaches to calculating edge weights from the adjacency matrix.

Usage

edge_weight_inverse(adj_mat, alpha = 1)

edge_weight_negative_log(adj_mat, alpha = 1)

edge_weight_linear(adj_mat, max_co_responses = NULL)

edge_weight_power(adj_mat, beta = 0.5, alpha = 1)

edge_weight_exponential(adj_mat, lambda = 0.1, alpha = 1)

Arguments

adj_mat

The adjacency matrix where entry i,j is the number of co-responses between items i and j

alpha

Smoothing parameter for avoiding division by zero

max_co_responses

Scaling factor for linear weighting

beta

Exponent for power transformation

lambda

Decay constant for exponential decay weighting

Value

A matrix of edge weights for use in distance calculations

Examples

adj_mat <- matrix(c(3, 1, 1, 2), nrow = 2)
edge_weight_inverse(adj_mat)
#>      [,1]      [,2]
#> [1,] 0.25 0.5000000
#> [2,] 0.50 0.3333333