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TDNN weights (choose method, k = 1), distance-based ranking

Source: R/api-weights.R
weights_tdnn.Rd

Unified entry point for TDNN weights. Use method = "exact" for the exact finite-population rank-weight rule (weights_tdnn_exact()) and method = "asymp" for the asymptotic full-rank approximation (weights_tdnn_asymp()).

Usage

weights_tdnn(
  X,
  X0 = NULL,
  x0 = NULL,
  distance = "l2",
  s1,
  s2,
  dim = NULL,
  method = c("exact", "asymp"),
  normalize = TRUE,
  ctx = NULL,
  return = c("W")
)

Arguments

X

Numeric matrix (n x p).

X0

Numeric matrix (m x p); mutually exclusive with x0.

x0

Numeric length-p single target (convenience for m = 1).

distance

Distance spec or registered name (e.g., "l2").

s1

Positive integer; smaller U-statistic order (s1 < s2 <= n).

s2

Positive integer; larger U-statistic order.

dim

Positive integer; localization dimension. Defaults to ncol(X) when NULL.

method

One of "exact" or "asymp".

normalize

Logical; renormalize rank table columns to sum 1 (default TRUE).

ctx

Optional context passed through to distance and rank-weight evaluators.

return

Character vector of extras to include; any of c("W", "ord", "ranks", "dx").

Value

A weights_result object.

See also

weights_tdnn_exact(), weights_tdnn_asymp()

Examples

set.seed(1)
X  <- matrix(rnorm(30), 15, 2)
x0 <- c(0, 0)
out <- weights_tdnn(X, x0 = x0, s1 = 3L, s2 = 6L, method = "exact")
colSums(out$W)  # 1
#> [1] 1