Description Usage Format Note References See Also Examples

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

1 |

The `noRegMin`

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.

This dataset is artificial and included for illustrating regular
minimality being violated. It differs from the artificial data
`regMin`

only in the entry in row \#*9* and column
\#*10*.

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/.

`regMin`

for the other artificial data satisfying
regular minimality in non-canonical form; `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.

1 2 3 | ```
## dataset noRegMin violates regular minimality
noRegMin
check.regular(noRegMin, type = "reg.minimal")
``` |

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