Packaged: 2021-10-14 07:44:22 UTC; adamsparks

Packaged: 2022-08-14 00:42:00 UTC; adamsparks

Description: Read data from the City of Portland's 'HYDRA' (http://or.water.usgs.gov/precip/) rainfall datasets within R.
Packaged: 2015-12-15 14:02:03 UTC; ironholds

Description: Read data from the City of Portland's 'HYDRA' <http://or.water.usgs.gov/precip/> rainfall datasets within R.
Packaged: 2017-01-05 00:17:10 UTC; ironholds

Title: Authenticated HTTP Request Client for the 'Hakai' API
Description: Initializes a class that obtains API credentials and provides
a method to use those credentials to make GET requests to the 'Hakai'
API server. Usage instructions are documented at

person("Taylor", "Denouden", , "taylor.denouden@hakai.org", role = c("aut", "cre")),
person("Brett", "Johnson", , "brett.johnson@hakai.org", role = "aut"),
person("Nate", "Rosenstock", , "nate.rosenstock@hakai.org", role = "ctb"),
person("Chris", "Davis", , "chris.davis@hakai.org", role = "ctb")

Title: The Scalable Highly Adaptive Lasso
person("Oleg", "Sofrygin", email = "oleg.sofrygin@gmail.com",
person("Weixin", "Cai", email = "wcai@berkeley.edu",
Description: A scalable implementation of the highly adaptive lasso algorithm,
including routines for constructing sparse matrices of basis functions of the
observed data, as well as a custom implementation of Lasso regression tailored
to enhance efficiency when the matrix of predictors is composed exclusively of
indicator functions. For ease of use and increased flexibility, the Lasso
fitting routines invoke code from the 'glmnet' package by default. The highly
adaptive lasso was first formulated and described by MJ van der Laan (2017)
<doi:10.1515/ijb-2015-0097>, with practical demonstrations of its performance
given by Benkeser and van der Laan (2016) <doi:10.1109/DSAA.2016.93>.
Imports: Matrix, stats, utils, methods, assertthat, origami (>= 0.8.1),
Suggests: testthat, knitr, rmarkdown, microbenchmark, future, ggplot2,
dplyr, tidyr, stringr, survival, data.table, SuperLearner
Author: Jeremy Coyle [aut, cre] (<https://orcid.org/0000-0002-9874-6649>),