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This function is deprecated. Use build_network instead.

Usage

estimate_network(
  data,
  method = "relative",
  params = list(),
  scaling = NULL,
  threshold = 0,
  level = NULL,
  ...
)

Arguments

data

Data frame (sequences or per-observation frequencies) or a square symmetric matrix (correlation or covariance).

method

Character. Defaults to "relative" for backward compatibility.

params

Named list. Method-specific parameters passed to the estimator function (e.g. list(gamma = 0.5) for glasso, or list(format = "wide") for transition methods). This is the key composability feature: downstream functions like bootstrap or grid search can store and replay the full params list without knowing method internals.

scaling

Character vector or NULL. Post-estimation scaling to apply (in order). Options: "minmax", "max", "rank", "normalize". Can combine: c("rank", "minmax"). Default: NULL (no scaling).

threshold

Numeric. Absolute values below this are set to zero in the result matrix. Default: 0 (no thresholding).

level

Character or NULL. Multilevel decomposition for association methods. One of NULL, "between", "within", "both". Requires id_col. Default: NULL.

...

Additional arguments passed to build_network.

Value

A netobject (see build_network).

See also

Examples

# \donttest{
data <- data.frame(A = c("x","y","z","x"), B = c("y","x","z","y"))
net <- estimate_network(data, method = "relative")
#> Warning: 'estimate_network' is deprecated.
#> Use 'build_network' instead.
#> See help("Deprecated")
# }