Title: Models for analysing moult in birds

data, based on models developed in Underhill

Title: Mountain Plots, Folded Empirical Cumulative Distribution Plots
Description: Lattice functions for drawing folded empirical cumulative distribution plots, or mountain plots. A mountain plot is similar to an empirical CDF plot, except that the curve increases from 0 to 0.5, then decreases from 0.5 to 1 using an inverted scale at the right side.  See: Monti (1995), Folded empirical distribution function curves-mountain plots.  The American Statistician, 49, 342-345.
Packaged: 2015-01-26 12:43:32 UTC; wrightkevi

Description: Lattice functions for drawing folded empirical cumulative
distribution plots, or mountain plots. A mountain plot is similar
to an empirical CDF plot, except that the curve increases from
0 to 0.5, then decreases from 0.5 to 1 using an inverted scale at
the right side.  See: Monti (1995), Folded empirical distribution
function curves-mountain plots.  The American Statistician, 49, 342-345.
Packaged: 2015-07-02 18:42:34 UTC; wrightkevi

Packaged: 2017-07-12 22:45:18 UTC; wrightkevi

Suggests: knitr, latticeExtra, rmarkdown, testthat
Packaged: 2021-04-16 15:31:27 UTC; wrightkevi

Packaged: 2022-05-02 00:45:27 UTC; wrightkevi

Title: Mouse-Tracking Measures from Trajectory Data
Author: Moreno I. Coco and Nicholas D. Duran with contributions of Rick Dale, Denis O'Hora and Michael J. Spivey.
Description: Extract from two-dimensional x-y coordinates of an arm-reaching trajectory, several dependent measures such as area under the curve, latency to start the movement, x-flips, etc.; which characterize the action-dynamics of the response. Mainly developed to analyze data coming from mouse-tracking experiments.
Collate: 'angdiffvec.R' 'areaunder.R' 'getmouseDV.R' 'interpltraj.R'
'makerun.R' 'maxdev.R' 'pathoffset.R' 'sampen.R' 'sampenc.R'
'sampense.R' 'trim0.R' 'trim1.R' 'velaj.R' 'xflip.R'

Title: Process and Analyze Mouse-Tracking Data
Description: Mouse-tracking, the analysis of mouse movements in computerized
experiments, is a method that is becoming increasingly popular in the
cognitive sciences. The mousetrap package offers functions for importing,
preprocessing, analyzing, aggregating, and visualizing mouse-tracking data.
Maintainer: Pascal J. Kieslich <kieslich@psychologie.uni-mannheim.de>
person(c("Pascal","J."), "Kieslich", role= c("aut", "cre"),
person("Felix", "Henninger", role = "aut",
Imports: utils, stats, pracma, reshape2, graphics, grDevices, ggplot2,