inphr: Statistical Inference for Persistence Homology Data
A set of functions for performing null hypothesis testing on
samples of persistence diagrams using the theory of permutations. Currently,
only two-sample testing is implemented. Inputs can be either samples of
persistence diagrams themselves or vectorizations. In the former case, they
are embedded in a metric space using either the Bottleneck or Wasserstein
distance. In the former case, persistence data becomes functional data and
inference is performed using tools available in the 'fdatest' package. Main
reference for the interval-wise testing method: Pini A., Vantini S. (2017)
"Interval-wise testing for functional data" <doi:10.1080/10485252.2017.1306627>.
Main reference for inference on populations of networks: Lovato, I., Pini, A.,
Stamm, A., & Vantini, S. (2020) "Model-free two-sample test for network-valued
data" <doi:10.1016/j.csda.2019.106896>.
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