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

Title: Assess Medication Adherence from Pharmaceutical Claims Data
Authors@R: person("Brennan", "Beal", email = "brennanbeal@gmail.com",
Description: 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>.
Imports: Rcpp (>= 1.0.5), anytime, tidyr, dplyr, purrr, lubridate,

Title: calculate ad hoc distance thresholds for DNA barcoding
Description: An ad hoc distance threshold can be calculated for each particular reference library of DNA barcodes. Specimen identification at this ad hoc distance threshold (using the best close match method) will produce identifications with an estimated relative error probability that can be fixed by the user (e.g. 5%)
Depends: R (>= 2.15), spider, ape, polynom

Title: Calculate Ad Hoc Distance Thresholds for DNA Barcoding
Description: Two functions to calculate intra- and interspecific pairwise distances, evaluate DNA barcoding identification error and calculate an ad hoc distance threshold for each particular reference library of DNA barcodes. Specimen identification at this ad hoc distance threshold (using the best close match method) will produce identifications with an estimated relative error probability that can be fixed by the user (e.g. 5%).
Depends: R (>= 2.15), ape, pegas, polynom