MNREAD Parameters Estimation and Curve Plotting
Allows to analyze the reading data obtained with the MNREAD Acuity
Chart, a continuous-text reading acuity chart for normal and low vision.
Provides the necessary functions to plot the MNREAD curve and estimate
automatically the four MNREAD parameters: Maximum Reading Speed,
Critical Print Size, Reading Acuity and Reading Accessibility Index.
Reference: Calabrese et al. 2016 <doi:10.1001/jamaophthalmol.2015.6097>.

Allows to analyze the reading data obtained with the MNREAD Acuity
Chart, a continuous-text reading acuity chart for normal and low vision.
Provides the necessary functions to plot the MNREAD curve and estimate
automatically the four MNREAD parameters: Maximum Reading Speed,
Critical Print Size, Reading Acuity and Reading Accessibility Index.
Parameters can be estimated either with the standard method
or with a nonlinear mixed-effects (NLME) modeling.
See Calabrese et al. 2018 for more details <doi.org/10.1167/18.1.8>.

c(
person("Aurélie", "Calabrèse", email = "acalabre@umn.edu", role = c("aut", "cre")),
person("Gordon E.", "Legge", email = "legge@umn.edu", role = "aut")
)
Aurélie Calabrèse [aut, cre],
Gordon E. Legge [aut]

c(
person("Aurélie", "Calabrèse", email = "aurelie.calabrese@inria.fr", role = c("aut", "cre")),
person("J. Steve", "Mansfield", email = "steve.mansfield@plattsburgh.edu", role = "aut"),
person("Gordon E.", "Legge", email = "legge@umn.edu", role = "aut")
)
Allows to analyze the reading data obtained with the MNREAD Acuity
Chart, a continuous-text reading acuity chart for normal and low vision.
Provides the necessary functions to plot the MNREAD curve and estimate
automatically the four MNREAD parameters: Maximum Reading Speed,
Critical Print Size, Reading Acuity and Reading Accessibility Index.
Parameters can be estimated either with the standard method
or with a nonlinear mixed-effects (NLME) modeling.
See Calabrese et al. 2018 for more details <doi:10.1167/18.1.8>.

Multivariate Nonparametric Statistical Process Control
Martin Bezener <bezener@stat.umn.edu> and Peihua Qiu
<qiu@stat.umn.edu>
Statistical process control for multivariate data that is
not necessarily Gaussian distributed. A function is provided to
categorize components of multivariate response vectors. Tools
for setting up a CUSUM procedure for the transformed data are
included. The CUSUM scheme can also be applied to the case when
some (or all) of the multivariate response components are
binary-categorical.