| network_reliability | R Documentation |
Assesses the stability of network estimates by repeatedly splitting sequences into two halves, building networks from each half, and comparing them. Supports single-model reliability assessment and multi-model comparison with optional scaling for cross-method comparability.
For transition methods ("relative", "frequency",
"co_occurrence"), uses pre-computed per-sequence count matrices
for fast resampling (same infrastructure as
bootstrap_network).
network_reliability(
...,
iter = 1000L,
split = 0.5,
scale = "none",
seed = NULL
)
... |
One or more |
iter |
Integer. Number of split-half iterations (default: 1000). |
split |
Numeric. Fraction of sequences assigned to the first half (default: 0.5). |
scale |
Character. Scaling applied to both split-half matrices
before computing metrics. One of |
seed |
Integer or NULL. RNG seed for reproducibility. |
An object of class "net_reliability" containing:
Data frame with columns model, mean_dev,
median_dev, cor, max_dev (one row per iteration
per model).
Data frame with columns model, metric,
mean, sd.
Named list of the original netobjects.
Number of iterations.
Split fraction.
Scaling method used.
build_network, bootstrap_network
net <- build_network(data.frame(V1 = c("A","B","C","A"),
V2 = c("B","C","A","B")), method = "relative")
rel <- network_reliability(net, iter = 10)
seqs <- data.frame(
V1 = sample(LETTERS[1:4], 30, TRUE), V2 = sample(LETTERS[1:4], 30, TRUE),
V3 = sample(LETTERS[1:4], 30, TRUE), V4 = sample(LETTERS[1:4], 30, TRUE)
)
net <- build_network(seqs, method = "relative")
rel <- network_reliability(net, iter = 100, seed = 42)
print(rel)
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