Score Persons Using the Generalized Graded Unfolding Model
Estimate GGUM Person Parameters Using Pre-Calibrated Item Parameters and Binary or Graded Disagree-Agree Responses

Implementation of SCORE, SCORE+ and Mixed-SCORE
c(person("Jiashun Jin", role = 'aut', email = "jiashun@jiashun@cmu.edu"),
person("Zheng Tracy Ke", role = 'aut', email = "zke@fas.harvard.edu"),
person("Shengming Luo", role = c('aut', 'cre'), email = "shengmil@andrew.cmu.edu"))
Implementation of community detection algorithm SCORE in the paper J. Jin (2015) <arXiv:1211.5803>, and SCORE+ in J. Jin, Z. Ke and S. Luo (2018) <arXiv:1811.05927>. Membership estimation algorithm called Mixed-SCORE in J. Jin, Z. Ke and S. Luo (2017) <arXiv:1708.07852>.
utils, combinat, limSolve, RSpectra, igraph, igraphdata, stats
Jiashun Jin [aut],
Zheng Tracy Ke [aut],
Shengming Luo [aut, cre]

Enio Jelihovschi <eniojelihovs@gmail.com>
Jose Claudio Faria <joseclaudio.faria@gmail.com>
Sergio Oliveira <solive@uesc.br>
Multiple comparison test of means using the clustering method
of Scott & Knott

Enio Jelihovschi <eniojelihovs@gmail.com>, Jose Claudio Faria
<joseclaudio.faria@gmail.com> and Sergio Oliveira
<solive@uesc.br>
Division of an ANOVA experiment treatment means into
homogeneous distinct groups using the clustering method of
Scott & Knott

Enio Jelihovschi <eniojelihovs@gmail.com>, Jose Claudio Faria
<joseclaudio.faria@gmail.com> and Ivan Bezerra Allaman
<ivanalaman@gmail.com>

Enio Jelihovschi <eniojelihovs@gmail.com>
José Cláudio Faria <joseclaudio.faria@gmail.com>
Ivan Bezerra Allaman <ivanalaman@gmail.com>

Enio Jelihovschi, José Cláudio Faria and Ivan Bezerra Allaman
Division of an ANOVA experiment treatment means into homogeneous distinct groups using the clustering method of Scott & Knott.

Perform the balanced (Scott and Knott, 1974) and unbalanced <doi:10.1590/1984-70332017v17n1a1> Scott & Knott algorithm.

The Scott-Knott Effect Size Difference (ESD) Test
An enhancement of the Scott-Knott test (which cluster distributions
into statistically distinct ranks) that takes effect size into consideration.