ndl (version 0.2.18)

lexample: Lexical example data illustrating the Rescorla-Wagner equations

Description

Ten monomorphemic and inflected English words with fictive frequencies, and meanings.

Usage

data(lexample)

Format

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

Details

This example lexicon is used in Baayen et al. (2011) (table 8, figure 4) to illustrate the Rescorla-Wagner equations.

References

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.

See Also

RescorlaWagner, orthoCoding

Examples

# 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))
# }