A collection of privacy-preserving distributed algorithms for conducting multi-site data analyses. The regression analyses can be linear regression for continuous outcome, logistic regression for binary outcome, Cox proportional hazard regression for time-to event outcome, or Poisson regression for count outcome. The PDA algorithm runs on a lead site and only requires summary statistics from collaborating sites, with one or few iterations. For more information, please visit our software websites: <https://github.com/Penncil/pda>, and <https://penncil2019pda.wixsite.com/mysite>.

Permutation Distribution Clustering is a clustering method
for time series. Dissimilarity of time series is formalized as
the divergence between their permutation distributions. The
permutation distribution was proposed as measure of the
complexity of a time series.

Permutation Distribution Clustering is a clustering method for time series. Dissimilarity of time series is formalized as the divergence between their permutation distributions. The permutation distribution was proposed as measure of the complexity of a time series.

c(person(given = "Yves",      family = "Croissant",    role = c("aut", "cre"), email = "yves.croissant@univ-reunion.fr"),
person(given = "Giovanni",  family = "Millo",        role = "aut", email = "Giovanni.Millo@Generali.com"))
Data sets for the Panel Data Econometrics with R book.
Yves Croissant [aut, cre],
Giovanni Millo [aut]

car, dplyr, ggplot2, lmtest, msm, pglm, plm, splm, survival,
texreg
Data sets for the Panel Data Econometrics with R <doi:10.1002/9781119504641> book.

c(person(given = "Yves",
family = "Croissant",
role = c("aut", "cre"),
email = "yves.croissant@univ-reunion.fr",
comment = c(ORCID = "0000-0002-4857-7736")),
person(given = "Giovanni",
family = "Millo",
role = "aut",
email = "giovanni.millo@deams.units.it"))
car, dplyr, ggplot2, lmtest, msm, pglm, splm, survival,
texreg
Yves Croissant [aut, cre] (<https://orcid.org/0000-0002-4857-7736>),
Giovanni Millo [aut]