languages like Julia, Matlab/Octave, or Python+NumPy.

matrices), (ii) better printing of large matrices via a new generic function
for "pretty" printing, and (iii) a number of convenience functions for users
more familiar with other scientific languages like Julia, Matlab/Octave, or

more familiar with other scientific languages like 'Julia', 'Matlab'/'Octave',

Description: Additional matrix functionality for R including: (1) wrappers for
the base matrix function that allow matrices to be created from character
matrices), (2) better printing of large matrices via the generic "pretty"
print function, and (3) a number of convenience functions for users more
familiar with other scientific languages like 'Julia', 'Matlab'/'Octave', or

Title: Download and Read RAM Legacy Stock Assessment Database
email = "cboettig@gmail.com", comment = c(ORCID = "http://orcid.org/0000-0002-1642-628X")),
email = "sam.albers@gmail.com", comment = c(ORCID = "https://orcid.org/0000-0002-9270-7884")),
email = "afflerbach@nceas.ucsb.edu", comment = c(ORCID = "https://orcid.org/0000-0002-5215-9342")),
person(given = "RAM Legacy Stock Assessment Database",
Description: Contains functions to download, cache and read in 'Excel' version of the
RAM Legacy Stock Assessment Data Base, an online compilation of stock assessment
results for commercially exploited marine populations from around the world.
The database is named after Dr. Ransom A. Myers whose original stock-recruitment database,
is no longer being updated. More information about the database can be found at
Suggests: covr, testthat, httptest, knitr, rmarkdown
Author: Carl Boettiger [aut, cph] (<https://orcid.org/0000-0002-1642-628X>),
RAM Legacy Stock Assessment Database [dtc]

Title: Bayesian Geostatistical Modeling with RAMPS
Author: Brian J. Smith <brian-j-smith@uiowa.edu>,
Description: Bayesian geostatistical modeling of Gaussian processes using a reparameterized and marginalized posterior sampling (RAMPS) algorithm designed to lower autocorrelation in MCMC samples.  Package performance is tuned for large spatial datasets.
Packaged: Mon Sep 24 14:06:00 2007; bjsmith