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, orlist(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". Requiresid_col. Default:NULL.- ...
Additional arguments passed to
build_network.
Value
A netobject (see build_network).
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")
# }