Description Usage Format References Examples

Lexical distributional measures for 2233 English monomorphemic words. This dataset provides
a subset of the data available in the dataset `english`

.

1 |

A data frame with 2233 observations on the following 24 variables.

`Word`

a factor with 2284 words.

`CelS`

numeric vector with log-transformed lemma frequency in the CELEX lexical database.

`Fdif`

numeric vector with the logged ratio of written frequency (CELEX) to spoken frequency (British National Corpus).

`Vf`

numeric vector with log morphological family size.

`Dent`

numeric vector with derivational entropy.

`Ient`

numeric vector with inflectional entropy.

`NsyS`

numeric vector with the log-transformed count of synonym sets in WordNet in which the word is listed.

`NsyC`

numeric vector with the log-transformed count of synonym sets in WordNet in which the word is listed as part of a compound.

`Len`

numeric vector with length of the word in letters.

`Ncou`

numeric vector with orthographic neighborhood density.

`Bigr`

numeric vector with mean log bigram frequency.

`InBi`

numeric vector with log frequency of initial diphone.

`spelV`

numeric vector with type count of orthographic neighbors.

`spelN`

numeric vector with token count of orthographic neighbors.

`phonV`

numeric vector with type count of phonological neighbors.

`phonN`

numeric vector with token count of phonological neighbors.

`friendsV`

numeric vector with type counts of consistent words.

`friendsN`

numeric vector with token counts of consistent words.

`ffV`

numeric vector with type count of forward inconsistent words.

`ffN`

numeric vector with token count of forward inconsistent words.

`fbV`

numeric vector with type count of backward inconsistent words.

`fbN`

numeric vector with token count of backward inconsistent words

`ffNonzero`

a numeric vector with the count of forward inconsistent words with nonzero frequency.

`NVratio`

a numeric vector with the logarithmically transformed ratio of the noun and verb frequencies.

Baayen, R.H., Feldman, L. and Schreuder, R. (2006)
Morphological influences on the recognition of monosyllabic
monomorphemic words, *Journal of Memory and Language*,
53, 496-512.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
## Not run:
data(lexicalMeasures)
data(lexicalMeasuresDist)
library(rms)
library(cluster)
plot(varclus(as.matrix(lexicalMeasures[,-1])))
lexicalMeasures.cor = cor(lexicalMeasures[,-1], method = "spearman")^2
lexicalMeasures.dist = dist(lexicalMeasures.cor)
pltree(diana(lexicalMeasures.dist))
data(lexicalMeasuresClasses)
x = data.frame(measure = rownames(lexicalMeasures.cor),
cluster = cutree(diana(lexicalMeasures.dist), 5),
class = lexicalMeasuresClasses$Class)
x = x[order(x$cluster), ]
x
## End(Not run)
``` |

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