| finalDevoicing | R Documentation |
Phonological specifications for onset, nucleus and offset for 1697 Dutch monomorphemic words with a final obstruent. These final obstruents may exhibit a voicing alternation that is traditionally described as syllable-final devoicing: underlying /d/ in /hond/ becomes a /t/ when syllable-final ([hOnt]) and remains a /d/ otherwise ([hOn-den]).
data(finalDevoicing)
A data frame with 1697 observations on the following 9 variables.
Worda factor with the words as levels.
Onset1Typea factor for the first consonant in the onset, with levels None,
Obstruent and Sonorant.
Onset2Typea factor for the second consonant in the onset, with levels None,
Obstruent and Sonorant.
VowelTypea factor describing the vowel with levels iuy, long and
short.
ConsonantTypea factor for the first consonant in the offset, with levels None,
Obstruent and Sonorant.
Obstruenta factor describing place and manner of articulation of the final obstruent,
with levels F (/f,v/), P (/p,b/), S (/s,z/), T (/t,d/) and
X (/x,g/).
Nsylla numeric vector for the number of syllables in the word.
Stressa factor with levels A (antepenult), F (final) and
P (penult).
Voicea factor with levels voiced and voiceless.
Ernestus, M. and Baayen, R. H. (2003) Predicting the unpredictable: Interpreting neutralized segments in Dutch, Language, 79, 5-38.
## Not run:
data(finalDevoicing)
library(rpart)
# ---- CART tree
finalDevoicing.rp = rpart(Voice ~ ., data = finalDevoicing[ , -1])
plotcp(finalDevoicing.rp)
finalDevoicing.pruned = prune(finalDevoicing.rp, cp = 0.021)
plot(finalDevoicing.pruned, margin = 0.1, compress = TRUE)
text(finalDevoicing.pruned, use.n = TRUE, pretty = 0, cex=0.8)
# ---- logistic regression
library(rms)
finalDevoicing.dd = datadist(finalDevoicing)
options(datadist='finalDevoicing.dd')
finalDevoicing.lrm = lrm(Voice ~ VowelType + ConsonantType + Obstruent +
Nsyll + Stress + Onset1Type + Onset2Type, data = finalDevoicing)
anova(finalDevoicing.lrm)
# ---- model simplification
fastbw(finalDevoicing.lrm)
finalDevoicing.lrm = lrm(Voice ~ VowelType + ConsonantType +
Obstruent + Nsyll, data = finalDevoicing, x = TRUE, y = TRUE)
plot(Predict(finalDevoicing.lrm))
# ---- model validation
validate(finalDevoicing.lrm, B = 200)
## End(Not run)
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