badCoded: Nishisato and Clavel, artificial set of data

Description Usage Format Source References Examples

Description

10 observation and 3 variables erroneously coded.

Usage

1

Format

A data frame with 10 observations on the following 3 variables.

V2

Option 1 is omited

V3

Options go from 1 to 8

V4

Option 1 omited, other are not consecutive and there is NA

Source

Nishisato S, Baba Y (1999). On contingency, projection and forced classification of dual scaling. Behaviormetrika, 26, 207–219.

References

Nishisato S (2007). Multidimensional Nonlinear Descriptive Analysis. Chapman & Hall/CRC.

Examples

1
2

Example output

Loading required package: matrixcalc
Loading required package: ff
Loading required package: bit
Attaching package bit
package:bit (c) 2008-2012 Jens Oehlschlaegel (GPL-2)
creators: bit bitwhich
coercion: as.logical as.integer as.bit as.bitwhich which
operator: ! & | xor != ==
querying: print length any all min max range sum summary
bit access: length<- [ [<- [[ [[<-
for more help type ?bit

Attaching package: 'bit'

The following object is masked from 'package:base':

    xor

Attaching package ff
- getOption("fftempdir")=="/work/tmp/tmp/RtmpIchVdT"

- getOption("ffextension")=="ff"

- getOption("ffdrop")==TRUE

- getOption("fffinonexit")==TRUE

- getOption("ffpagesize")==65536

- getOption("ffcaching")=="mmnoflush"  -- consider "ffeachflush" if your system stalls on large writes

- getOption("ffbatchbytes")==16777216 -- consider a different value for tuning your system

- getOption("ffmaxbytes")==536870912 -- consider a different value for tuning your system


Attaching package: 'ff'

The following objects are masked from 'package:bit':

    clone, clone.default, clone.list

The following objects are masked from 'package:utils':

    write.csv, write.csv2

The following objects are masked from 'package:base':

    is.factor, is.ordered

Loading required package: vcd
Loading required package: grid
Loading required package: lattice
Loading required package: Matrix

------------
You had NA values in your Initial Dataset. 
 Chose rad/act correction mode.
------------
Beware, radical action has been taken!
$InitialData
   V2 V3 V4
1   3  1  2
2   2  1  3
3   2  1  2
4   4  2  2
5   3  1  2
6   4  8  2
7   2  1  2
8   2  1  2
9   4  2  7
10  3  1 NA

$TData
  V2 V3 V4
1  3  1  2
2  2  1  3
3  2  1  2
4  4  2  2
5  3  1  2
6  4  8  2
7  2  1  2
8  2  1  2
9  4  2  7

dualScale documentation built on May 29, 2017, 9:29 a.m.