| lexicalMeasures | R Documentation |
Lexical distributional measures for 2233 English monomorphemic words. This dataset provides
a subset of the data available in the dataset english.
data(lexicalMeasures)
A data frame with 2233 observations on the following 24 variables.
Worda factor with 2284 words.
CelSnumeric vector with log-transformed lemma frequency in the CELEX lexical database.
Fdifnumeric vector with the logged ratio of written frequency (CELEX) to spoken frequency (British National Corpus).
Vfnumeric vector with log morphological family size.
Dentnumeric vector with derivational entropy.
Ientnumeric vector with inflectional entropy.
NsySnumeric vector with the log-transformed count of synonym sets in WordNet in which the word is listed.
NsyCnumeric vector with the log-transformed count of synonym sets in WordNet in which the word is listed as part of a compound.
Lennumeric vector with length of the word in letters.
Ncounumeric vector with orthographic neighborhood density.
Bigrnumeric vector with mean log bigram frequency.
InBinumeric vector with log frequency of initial diphone.
spelVnumeric vector with type count of orthographic neighbors.
spelNnumeric vector with token count of orthographic neighbors.
phonVnumeric vector with type count of phonological neighbors.
phonNnumeric vector with token count of phonological neighbors.
friendsVnumeric vector with type counts of consistent words.
friendsNnumeric vector with token counts of consistent words.
ffVnumeric vector with type count of forward inconsistent words.
ffNnumeric vector with token count of forward inconsistent words.
fbVnumeric vector with type count of backward inconsistent words.
fbNnumeric vector with token count of backward inconsistent words
ffNonzeroa numeric vector with the count of forward inconsistent words with nonzero frequency.
NVratioa 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.
## 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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