ade4 (>= 1.7-13), adegraphics, adephylo, sp, spdep, lattice,
methods, grDevices, graphics, MASS, stats, utils, shiny, vegan

Stéphane Dray, David Bauman, Guillaume Blanchet, Daniel Borcard,
Sylvie Clappe, Guillaume Guenard, Thibaut Jombart, Guillaume Larocque,
Pierre Legendre, Naima Madi, Helene H Wagner
Tools for the multiscale spatial analysis of multivariate data.
Several methods are based on the use of a spatial weighting matrix and its
eigenvector decomposition (Moran's Eigenvectors Maps, MEM).
Several approaches are described in the review Dray et al (2012)
<doi:10.1890/11-1183.1>.

Tools for the multiscale spatial analysis of multivariate data.
Several methods are based on the use of a spatial weighting matrix and its
eigenvector decomposition (Moran's Eigenvectors Maps, MEM).
Several approaches are described in the review Dray et al (2012) <doi:10.1890/11-1183.1>.

Import from and Export to Amiga Disk Files
Amiga Disk Files (ADF) are virtual
representations of 3.5 inch floppy disks for the
Commodore Amiga. Most disk drives from other systems
(including modern drives) are not able to read these
disks. To be able to emulate this system, the ADF
format was created. This package enables you to read
ADF files and import and export files from and to such
virtual DOS-formatted disks.

Get Adform Ads Data via the 'Windsor.ai' API
c(
person("Pablo", "Sanchez", email = "pablosama@outlook.es", role = c("cre","aut")),
person("Windsor.ai", email = "admin@windsor.ai", role = "cph"))
Collect  your data on digital marketing campaigns from Adform Ads using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.
knitr, rmarkdown, dplyr, ggplot2, tidyr, curl
Pablo Sanchez [cre, aut],
Windsor.ai [cph]

Assess Medication Adherence from Pharmaceutical Claims Data
person("Brennan", "Beal", email = "brennanbeal@gmail.com",
role = c("aut", "cre"))
A (mildly) opinionated set of functions to help assess medication adherence for researchers working with medication claims data.
Medication adherence analyses have several complex steps that are often convoluted and can be time-intensive. The focus is to create a
set of functions using "tidy principles" geared towards transparency, speed, and flexibility while working with adherence metrics. All functions perform exactly one task
with an intuitive name so that a researcher can handle details (often achieved with vectorized solutions) while we handle non-vectorized tasks common to most
adherence calculations such as adjusting fill dates and determining episodes of care. The methodologies in referenced in this package come from
Canfield SL, et al (2019) "Navigating the Wild West of Medication Adherence Reporting in Specialty Pharmacy" <doi:10.18553/jmcp.2019.25.10.1073>.
Rcpp (>= 1.0.5), anytime, tidyr, dplyr, purrr, lubridate,
rlang