Software & Data
To track the most recent versions or update, visit my GitHub site.
1. R-package {capn}: Capital Asset Pricing for Nature
Download:
Installer (06-05-2017: v.1.0.0): available from R-CRAN
From R-CRAN: install.packages("capn")
From GitHub: devtools::install_github("ysd2004/capn")
Citation Instruction:
Yun, S. D., E. P. Fenichel, and J. K. Abbott, 2017, capn: Capital Asset Pricing for Nature (R Package), https://cran.r-project.org/web/packages/capn/index.html.
As capn is continually evolving, you may want to cite its version number. Find it with "help(package=capn)".
Author:
Seong D. Yun, Assistant Professor, Mississippi State University (seong.yun@msstate.edu)
Eli P. Fenichel, Professor, Yale University (eli.fenichel@yale.edu)
Joshua K. Abbott, Professor, Arizona State University (joshua.k.abbott@asu.edu)
Description:
A collection of functions that implements the approximation methods for natural capital asset prices suggested by Fenichel and Abbott (2014) in Journal of the Associations of Environmental and Resource Economists, Fenichel et al. (2016) in Proceedings of the National Academy of Sciences, and a third method, and its extensions to multiple stocks (where feasible): creating Chebyshev polynomial nodes and grids, calculating basis of Chebyshev polynomials, approximation and their simulations for: V-approximation (single and multiple stocks), P-approximation (single stock, PNAS), and Pdot-approximation (single stock, JAERE).
2. R-package {acdcR}: Agro-Climatic Data by County
Download:
Installer (06-27-2022: v.1.0.0): available from R-CRAN
From R-CRAN: install.packages("acdcR")
From GitHub: devtools::install_github("ysd2004/acdcR")
Citation Instruction:
Yun, S. D., 2022, acdcR: Agro-Climatic Data by County (R Package), https://cran.r-project.org/web/packages/acdcR/index.html.
Author:
Seong D. Yun, Assistant Professor, Mississippi State University (seong.yun@msstate.edu)
Description:
An R-package Agro-Climatic Data by County (acdcR) is designed to provide the functions to calculate the most widely-used county-level variables in agricultural production and agro-climatic and weather analyses. acdcR applies the most recent NLCD maps (2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019) to take account of agricultural areas only weighted averages over the PRISM rasters. In the current version of acdcR, there are functions to calculate growing season degree days (GDDs) wigh single/double sine/triangulation methods, to produce GDDs and precipitations by the PRISM grids or County FIPS codes from the direct input of PRSIM rasters, and to convert the PRISM grids data to county-level values.