c(
person(c("Alex", "M"), "Chubaty", email="alexander.chubaty@canada.ca",
role=c("aut", "cre")),
person("Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada",
role="cph")
)

c(
person(c("Alex", "M"), "Chubaty", email="alex.chubaty@gmail.com",
role=c("aut", "cre")),
person("Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada",
role="cph")
)
Comparisons of floating point numbers are problematic due to errors
associated with the binary representation of decimal numbers.
Despite being aware of these problems, people still use numerical methods
that fail to account for these and other rounding errors (this pitfall is
the first to be highlighted in Circle 1 of Burns (2012)
'The R Inferno' <http://www.burns-stat.com/pages/Tutor/R_inferno.pdf>).
This package provides new relational operators useful for performing
floating point number comparisons with a set tolerance.

c(
person(c("Alex", "M"), "Chubaty", email="achubaty@for-cast.ca",
role=c("aut", "cre"), comment = c(ORCID = "0000-0001-7146-8135")),
person(paste("Her Majesty the Queen in Right of Canada,",
"as represented by the Minister of Natural Resources Canada"),
role="cph")
)
Comparisons of floating point numbers are problematic due to errors
associated with the binary representation of decimal numbers.
Despite being aware of these problems, people still use numerical methods
that fail to account for these and other rounding errors (this pitfall is
the first to be highlighted in Circle 1 of Burns (2012)
'The R Inferno' <https://www.burns-stat.com/pages/Tutor/R_inferno.pdf>).
This package provides new relational operators useful for performing
floating point number comparisons with a set tolerance.

Spatio-temporal Fixation Pattern Analysis (FPA) is a new method of analyzing eye
movement data, developed by Mr. Jinlu Cao under the supervision of Prof. Chen Hsuan-Chih at
The Chinese University of Hong Kong, and Prof. Wang Suiping at the South China Normal
Univeristy. The package "fpa" is a R implementation which makes FPA analysis much easier.
There are four major functions in the package: ft2fp(), get_pattern(), plot_pattern(), and
lineplot(). The function ft2fp() is the core function, which can complete all the preprocessing
within moments. The other three functions are supportive functions which visualize the eye
fixation patterns.