Estimators for fuzzy linear regression. The functions estimate parameters of
fuzzy linear regression models with crisp or fuzzy independent variables (triangular
fuzzy numbers are supported). Implements multiple methods for parameter estimation and
algebraic operations with triangular fuzzy numbers. Includes functions for
summarising, printing and plotting the model fit. Calculates predictions from the
model and total error of fit.
Diamond (1988) <doi:10.1016/0020-0255(88)90047-3>,
Hung & Yang (2006) <doi:10.1016/j.fss.2006.08.004>,
Lee & Tanaka (1999) <doi:10.15807/jorsj.42.98>,
Nasrabadi, Nasrabadi & Nasrabady (2005) <doi:10.1016/j.amc.2004.02.008>,
Skrabanek, Marek & Pozdilkova (2021) <doi:10.3390/math9060685>,
Tanaka, Hayashi & Watada (1989) <doi:10.1016/0377-2217(89)90431-1>,
Zeng, Feng & Li (2017) <doi:10.1016/j.asoc.2016.09.029>.

Fuzzy string matching implementation of the 'fuzzywuzzy' <https://github.com/seatgeek/fuzzywuzzy> 'python' package. It uses the Levenshtein Distance <https://en.wikipedia.org/wiki/Levenshtein_distance> to calculate the differences between sequences.
Python (>= 2.4), difflib, fuzzywuzzy ( >=0.15.0 ),
python-Levenshtein ( >=0.12.0 ). Detailed installation
instructions for each operating system can be found in the
README file.

c( person(given = "Lampros", family = "Mouselimis", email = "mouselimislampros@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "https://orcid.org/0000-0002-8024-1546")), person("SeatGeek", "Inc", role = "cph"))
Lampros Mouselimis [aut, cre] (<https://orcid.org/0000-0002-8024-1546>),
SeatGeek Inc [cph]

An implementation of the fractional weighted bootstrap to be used as a drop-in for functions in
the 'boot' package. The fractional weighted bootstrap (also known as the Bayesian bootstrap) involves drawing
weights randomly that are applied to the data rather than resampling units from the data. See Xu et al. (2020)
<doi:10.1080/00031305.2020.1731599> for details.
survival, boot, sandwich (>= 2.4-0), lmtest, parallel