transform_weights: Transform Edge Weights for PageRank

In pagerankr: Modular Toolkit for PageRank Calculation

Transform Edge Weights for PageRank

Description

Applies a transformation strategy to a numeric vector of edge weights before passing them to pagerank. Useful for converting link positions, click counts, or other raw signals into weights suitable for the PageRank random surfer model.

Usage

transform_weights(
  x,
  method = c("none", "log", "percentile", "minmax", "zipf", "rank_linear"),
  alpha = 1,
  offset = 1,
  floor_value = 0.01,
  descending = TRUE
)

Arguments

x	Numeric vector of raw weights (e.g., link positions on a page, GA4 click counts, or any positive numeric signal).
method	Character, the transformation strategy. One of: "none" Return x unchanged. "log" Apply log(x + offset) to compress large ranges (e.g., GA4 click counts spanning 1 to 100,000). The offset parameter (default 1) avoids log(0). "percentile" Map values to their empirical percentile (0–1). Robust to extreme outliers. "minmax" Scale to the [0, 1] range using min-max normalization. A small floor (floor_value, default 0.01) is added so that the lowest-weighted edge still carries some weight rather than zero. "zipf" Convert to rank order, then apply Zipf's law: weight = 1 / rank^alpha. Position 1 gets 1.0, position 2 gets 1/2^alpha, etc. Controlled by the alpha parameter (default 1). "rank_linear" Convert to rank order (1 = highest value), then assign linearly decreasing weights: weight = (n - rank + 1) / n. Position 1 gets 1.0, position n gets 1/n.
alpha	Numeric, exponent for the "zipf" method. Default 1.0. Higher values make the drop-off steeper (position 1 dominates more).
offset	Numeric, added to x before the "log" transform. Default 1 (so that zero-valued inputs produce log(1) = 0 rather than -Inf).
floor_value	Numeric, minimum weight for the "minmax" method. Default 0.01.
descending	Logical. For rank-based methods ("rank_linear", "zipf"), whether higher input values get higher weights. Default TRUE (e.g., if the input is click counts, more clicks = higher weight). Set to FALSE when the input is link position on a page (position 1 = most valuable, but numerically smallest).

Value

Numeric vector of the same length as x with transformed weights. NA values in x are preserved as NA in the output.

Examples

# Link positions on a page (1 = top, most valuable)
positions <- c(1, 2, 3, 4, 5)
transform_weights(positions, "rank_linear", descending = FALSE)
transform_weights(positions, "zipf", alpha = 1, descending = FALSE)
transform_weights(positions, "zipf", alpha = 2, descending = FALSE)

# GA4 click counts (wide range)
clicks <- c(50000, 12000, 800, 150, 3)
transform_weights(clicks, "log")
transform_weights(clicks, "minmax")
transform_weights(clicks, "zipf")

# Use with pagerank()
edges <- data.frame(
  from = c("Home", "Home", "Home"),
  to = c("About", "Blog", "Contact"),
  position = c(1, 2, 5)
)
edges$weight <- transform_weights(edges$position, "zipf",
  descending = FALSE
)
# pagerank(edges, weight_col = "weight", clean_edge_urls = FALSE)

pagerankr documentation built on Oct. 1, 2026, 5:09 p.m.