Description Details Author(s) References

Fechnerian scaling is a procedure for constructing a metric on a set
of objects (e.g., symbols, X-ray films). The constructed Fechnerian
metric represents subjective dissimilarities among the objects as
perceived by a system (e.g., person, technical device). The package
fechner provides functions and example datasets for performing
and illustrating Fechnerian scaling of discrete object sets in **R**.

Package: | fechner |

Type: | Package |

Version: | 1.0-3 |

Date: | 2016-06-05 |

License: | GPL (>= 2) |

Fechnerian scaling of discrete object (or stimulus) sets provides a
theoretical framework for deriving, so-called Fechnerian, distances
among objects representing subjective dissimilarities. A Fechnerian
metric on a set of stimuli is constructed from the probabilities
with which the objects are discriminated from each other by a
perceiving system. In addition to the oriented and overall
Fechnerian distances, the package fechner also computes such
related information as the points of subjective equality, the
psychometric increments, the geodesic chains and loops with their
corresponding lengths, and the generalized Shepardian
dissimilarities (or *S*-index). Moreover, the package
fechner provides functions for checking the required data
format and the fundamental regular minimality/maximality condition.
These concepts are explained in detail in the paper about the
fechner package by Uenlue, Kiefer, and Dzhafarov
(2009), and in the theoretical papers by Dzhafarov and
Colonius (2006, 2007) (see ‘References’).

The package fechner is implemented based on the S3 system. It
comes with a namespace, and consists of three external functions
(functions the package exports): `check.data`

,
`check.regular`

, and the main function of this package,
`fechner`

. It also contains six internal functions
(functions not exported by the package), which are `plot`

,
`print`

, and `summary`

methods for objects of the class
`fechner`

, a `print`

method for objects of the class
`summary.fechner`

, and two functions for computing intermediate
graph-theoretic information: `plot.fechner`

,
`print.fechner`

, `summary.fechner`

,
`print.summary.fechner`

, and fechner-internal.
The features of the package fechner are illustrated with
accompanying two real datasets, `morse`

and
`wish`

, and two artificial datasets,
`regMin`

and `noRegMin`

.

Thomas Kiefer, Ali Uenlue. Based on original MATLAB source by Ehtibar N. Dzhafarov.

Maintainer: Ali Uenlue <[email protected]>

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/.

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

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