Description Usage Format Details References See Also Examples
Ten monomorphemic and inflected English words with fictive frequencies, and meanings.
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A data frame with 10 observations on the following 3 variables:
Word
A character vector specifying word forms
Frequency
A numeric vector with the – fictive – frequencies of occurrence of the words
Outcomes
A character vector specifying the meaning components of the words, separated by underscores
This example lexicon is used in Baayen et al. (2011) (table 8, figure 4) to illustrate the Rescorla-Wagner equations.
Baayen, R. H., Milin, P., Filipovic Durdevic, D., Hendrix, P. and Marelli, M. (2011), An amorphous model for morphological processing in visual comprehension based on naive discriminative learning. Psychological Review, 118, 438-482.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ## Not run:
data(lexample)
lexample$Cues <- orthoCoding(lexample$Word, grams=1)
par(mfrow=c(2,2))
lexample.rw <- RescorlaWagner(lexample, nruns=25, traceCue="h",traceOutcome="hand")
plot(lexample.rw)
mtext("h - hand", 3, 1)
lexample.rw <- RescorlaWagner(lexample, nruns=25, traceCue="s",traceOutcome="plural")
plot(lexample.rw)
mtext("s - plural", 3, 1)
lexample.rw <- RescorlaWagner(lexample, nruns=25, traceCue="a",traceOutcome="as")
plot(lexample.rw)
mtext("a - as", 3, 1)
lexample.rw <- RescorlaWagner(lexample, nruns=25, traceCue="s",traceOutcome="as")
plot(lexample.rw)
mtext("s - as", 3, 1)
par(mfrow=c(1,1))
## End(Not run)
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