Provides a suite of functions that fit models that use PPM type priors for partitions. Models include hierarchical Gaussian and probit ordinal models with a (covariate dependent) PPM. If a covariate dependent product partition model is selected, then all the options detailed in Page, G.L.; Quintana, F.A. (2018) <doi:10.1007/s11222-017-9777-z> are available. If covariate values are missing, then the approach detailed in Page, G.L.; Quintana, F.A.; Mueller, P (2020) <doi:10.1080/10618600.2021.1999824> is employed. Also included in the package is a function that fits a Gaussian likelihood spatial product partition model that is detailed in Page, G.L.; Quintana, F.A. (2016) <doi:10.1214/15-BA971>, and multivariate PPM change point models that are detailed in Quinlan, J.J.; Page, G.L.; Castro, L.M. (2023) <doi:10.1214/22-BA1344>. In addition, a function that fits a univariate or bivariate functional data model that employs a PPM or a PPMx to cluster curves based on B-spline coefficients is provided.
Package details |
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Author | Garritt L. Page [aut, cre, cph], Jose J. Quinlan [aut, cph], S. McKay Curtis [ctb, cph], Radford M. Neal [ctb, cph] |
Maintainer | Garritt L. Page <page@stat.byu.edu> |
License | GPL |
Version | 0.3.4 |
Package repository | View on CRAN |
Installation |
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