cl_agg: Weighted averaging within clusters of parameter draws

In projpred: Projection Predictive Feature Selection

Weighted averaging within clusters of parameter draws

Description

This function aggregates S parameter draws that have been clustered into S_{\mathrm{cl}} clusters by averaging across the draws that belong to the same cluster. This averaging can be done in a weighted fashion.

Usage

cl_agg(
  draws,
  cl = seq_len(nrow(draws)),
  wdraws = rep(1, nrow(draws)),
  eps_wdraws = 0
)

Arguments

draws	An S \times P matrix of parameter draws, with P denoting the number of parameters.
cl	A numeric vector of length S, giving the cluster indices for the draws. Draws that should be dropped (e.g., by thinning) need to have an NA in cl.
wdraws	A numeric vector of length S, giving the weights of the draws. It doesn't matter whether these are normalized (i.e., sum to 1) or not because internally, these weights are normalized to sum to 1 within each cluster. Draws that should be dropped (e.g., by thinning) can (but must not necessarily) have an NA in wdraws.
eps_wdraws	A positive numeric value (typically small) which will be used to improve numerical stability: The weights of the draws within each cluster are multiplied by 1 - eps_wdraws. The default of 0 should be fine for most cases; this argument only exists to help in those cases where numerical instabilities occur (which must be detected by the user; this function will not detect numerical instabilities itself).

Value

An S_{\mathrm{cl}} \times P matrix of aggregated parameter draws.

Examples

set.seed(323)
S <- 100L
P <- 3L
draws <- matrix(rnorm(S * P), nrow = S, ncol = P)
# Clustering example:
S_cl <- 10L
cl_draws <- sample.int(S_cl, size = S, replace = TRUE)
draws_cl <- cl_agg(draws, cl = cl_draws)
# Clustering example with nonconstant `wdraws`:
w_draws <- rgamma(S, shape = 4)
draws_cl <- cl_agg(draws, cl = cl_draws, wdraws = w_draws)
# Thinning example (implying constant `wdraws`):
S_th <- 50L
idxs_thin <- round(seq(1, S, length.out = S_th))
th_draws <- rep(NA, S)
th_draws[idxs_thin] <- seq_len(S_th)
draws_th <- cl_agg(draws, cl = th_draws)

projpred documentation built on Oct. 1, 2023, 1:07 a.m.