Francesc Badia Roca (ISGlobal) <francesc.badia@isglobal.org>,
David Moriña Soler (Catalan Institute of Oncology (ICO)-IDIBELL) <david.morina@uab.cat>
Fits a linear excess relative risk model by maximum likelihood, possibly including several variables and allowing for lagged exposures. Allow time dependent covariates.
survival, stats4, plyr, dplyr, reshape2, numDeriv, ggplot2

Get Seismic Data from the International Federation of Digital
Seismograph Networks
This package facilitates searching for and downloading seismic time series in miniSEED format (a minimalist version of the Standard for the Exchange of Earthquake Data) from International Federation of Digital Seismograph Networks repositories. This package can also be used to gather information about seismic networks (stations, channels, locations, etc) and find historical earthquake data (origins, magnitudes, etc).
c(person(given="Daniel C.",family="Bowman", role=c("aut", "cre"),
email="daniel.bowman@unc.edu"))

Space-Time Estimation of Forest Variables using the FIA Database
Hunter Stanke [aut, cre],
Andrew Finley [aut]
The goal of 'rFIA' is to increase the accessibility and use of the United States Forest Services (USFS) Forest Inventory and Analysis (FIA) Database by providing a user-friendly, open source toolkit to easily query and analyze FIA Data. Designed to accommodate a wide range of potential user objectives, 'rFIA' simplifies the estimation of forest variables from the FIA Database and allows all R users (experts and newcomers alike) to unlock the flexibility inherent to the Enhanced FIA design. Specifically, 'rFIA' improves accessibility to the spatio-temporal estimation capacity of the FIA Database by producing space-time indexed summaries of forest variables within user-defined population boundaries. Direct integration with other popular R packages (e.g., 'dplyr', 'tidyr', and 'sf') facilitates efficient space-time query and data summary, and supports common data representations and API design. The package implements design-based estimation procedures outlined by Bechtold & Patterson (2005) <doi:10.2737/SRS-GTR-80>, and has been validated against estimates and sampling errors produced by FIA 'EVALIDator'. Current development is focused on the implementation of spatially-enabled model-assisted estimators to improve population, change, and ratio estimates.
dplyr, stringr, sp, sf, tidyr (>= 1.0.0), parallel, ggplot2,
gganimate, methods, data.table, bit64, progress