# sparsecommunity 0.1.0

## New features

* `community_detect()`: unified spectral community detection for the stochastic
  block model (`model = "sbm"`, k-means on regularized Laplacian embedding) and
  the degree-corrected stochastic block model (`model = "dcsbm"`, spherical
  k-median on row-normalized embedding). Implements the algorithms of
  Lei and Rinaldo (2015).

* `estimate_K()`: Bethe--Hessian spectral estimator for the number of
  communities in sparse networks. Implements the method of Hwang (2023).

* `simulate_sbm()`, `simulate_dcsbm()`: simulation utilities for generating
  benchmark graphs under both models.

* `misclustering_rate()`: permutation-corrected misclustering rate (Hungarian
  algorithm via `clue`, greedy fallback otherwise).

* `plot_scree()`: scree plot of regularized Laplacian eigenvalues to guide
  selection of K.

* `plot()` S3 method for `"sparsecommunity"` objects: scatter plot of the
  spectral embedding colored by detected community.

* `print()` and `summary()` S3 methods for `"sparsecommunity"`,
  `"sbm_sim"`, and `"dcsbm_sim"` objects.
