Nonparametric Analysis of Clustered Multistate Processes // Nonparametric estimation of population-averaged transition probabilities, with cluster-bootstrap pointwise confidence intervals, simultaneous confidence bands, and two-sample Kolmogorov-Smirnov-type tests for clustered or independent multistate process data. Estimation follows Bakoyannis (2021) doi:10.1111/biom.13327; two-sample inference for the cluster- randomized and independent-samples designs follows Bakoyannis and Bandyopadhyay (2022) doi:10.1007/s10463-021-00819-x. Both methods use the working-independence Aalen-Johansen estimator. The package supports both progressive (acyclic) and non- monotone (e.g., illness-death with recovery) multistate processes, right censoring, left truncation, and informative cluster size. The user supplies data in interval format (one row per mutually-exclusive time interval per subject) and interacts with the package through a single formula-based function, patp().