# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "lzrq" in publications use:' type: software license: CC-BY-4.0 title: 'lzrq: Quantile Regression for Logarithmic Relationships with Non-Positive Outcome Values' version: 0.1.0 doi: 10.32614/CRAN.package.lzrq abstract: Provides the lzrq() function for estimating logarithmic regression slopes in quantile regression models, permitting the outcome variable to take on non-positive values. lzrq() conducts regression after replacing non-positive values with a sufficiently negative value. If the fitted values of a quantile regression on this transformed outcome are all greater than the negative value, then results are displayed. The resulting coefficients can be meaningfully interpreted as logarithmic intensive-margin relationships between the outcome variable and the independent variables, even with non-positive values in the outcome variable. If the condition does not hold for the specified quantile, then the command iteratively makes the value larger and checks again. After ten iterations where the condition does not hold, the functions return an error and suppress results. This is an automated adaptation of the algorithm described by Liu & Kaplan (2025) and implemented in the companion Stata command lzqreg, described in Fitzgerald et al. (2026) . authors: - family-names: Valenta given-names: David email: dvalenta@uottawa.ca - family-names: Fitzgerald given-names: Jack email: jackfitzgeraldresearch@gmail.com repository: https://jack-fitzgerald.r-universe.dev repository-code: https://github.com/jack-fitzgerald/lzrq commit: 9631ef605766be6f5631eb4dc59482df03b18405 url: https://github.com/jack-fitzgerald/lzrq date-released: '2026-06-17' contact: - family-names: Fitzgerald given-names: Jack email: jackfitzgeraldresearch@gmail.com