regMin: Artificial Data: Regular Minimality In Non-canonical Form

In fechner: Fechnerian Scaling of Discrete Object Sets

Description

Artificial data of fictitious ‘discrimination probabilities’ among 10 fictitious stimuli.

Usage

regMin

Format

The regMin data frame consists of 10 rows and 10 columns, representing the fictitious stimuli presented in the first and second observation area, respectively. Each number, a numeric, in the data frame is assumed to give the relative frequency of perceivers scoring ‘different’ to the row stimulus ‘followed’ by the column stimulus.

Note

This dataset is artificial and included for illustrating regular minimality in the non-canonical form. It differs from the artificial data noRegMin only in the entry in row \#9 and column \#10.

References

Dzhafarov, E. N. and Colonius, H. (2006) Reconstructing distances among objects from their discriminability. Psychometrika, 71, 365–386.

Dzhafarov, E. N. and Colonius, H. (2007) Dissimilarity cumulation theory and subjective metrics. Journal of Mathematical Psychology, 51, 290–304.

Uenlue, A. and Kiefer, T. and Dzhafarov, E. N. (2009) Fechnerian scaling in R: The package fechner. Journal of Statistical Software, 31(6), 1–24. URL http://www.jstatsoft.org/v31/i06/.

See Also

noRegMin for the other artificial data violating regular minimality; check.data for checking data format; check.regular for checking regular minimality/maximality; fechner, the main function for Fechnerian scaling. See also morse for Rothkopf's Morse code data, wish for Wish's Morse-code-like data, and fechner-package for general information about this package.

Examples

## dataset regMin satisfies regular minimality in non-canonical form
regMin
check.regular(regMin, type = "reg.minimal")

fechner documentation built on May 2, 2019, 8:49 a.m.