The Behavioral Change Point Analysis (BCPA) is a method of
identifying hidden shifts in the underlying parameters of a time series,
developed specifically to be applied to animal movement data which is
irregularly sampled.  The method is based on: E.
Gurarie, R. Andrews and K. Laidre A novel method for identifying
behavioural changes in animal movement data (2009) Ecology Letters 12:5
395-408.

Behavioral Change Point Analysis of Animal Movement
The Behavioral Change Point Analysis (BCPA) is a method of
identifying hidden shifts in the underlying parameters of a time series,
developed specifically to be applied to animal movement data which is
irregularly sampled.  The method is based on: E. Gurarie, R. Andrews and
K. Laidre A novel method for identifying behavioural changes in animal
movement data (2009) Ecology Letters 12:5 395-408. A development version is
on <https://github.com/EliGurarie/bcpa>. NOTE: the BCPA method may be useful
for any univariate, irregularly sampled Gaussian time-series, but animal
movement analysts are encouraged to apply correlated velocity change point
analysis as implemented in the smoove package, as of this writing on GitHub
at <https://github.com/EliGurarie/smoove>. An example of a univariate analysis
is provided in the UnivariateBCPA vignette.
knitr, lubridate, magrittr, circular, digest, rmarkdown

Bayesian Multiple Changepoint Detection Using Metadata
A Bayesian approach to detect mean shifts in AR(1) time series while accommodating metadata (if available). In addition, a linear trend component is allowed.

person("Thomas", "Roh", email = "thomas@roh.engineering", role = c("aut", "cre"))
Provides functions to utilize a command line utility that does bulk inserts and exports from SQL Server databases.

person(given = "Abdessabour",
family = "Moutik",
role = c("aut", "cre"),
email = "a.moutik@insea.ac.ma")
Get Moroccan Stock Prices (historical data and intraday
changes), Market and Sector Indices and bonds.
See <https://www.leboursier.ma/>.

Bayesian continuous reasssessment method (CRM) designs for Phase
I dose-finding trials.
This package implements a wide variety of one and
two-parameter Bayesian CRM designs. The program can run
interactively, allowing the user to enter outcomes after each
cohort has been recruited, or via simulation to assess
operating characteristics.