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
.
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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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