Description Usage Format Source References Examples
Data set with 10 English words of different (ad hoc) frequencies, each with a lexical meaning and a grammatical meaning.
1 |
A data frame with 10 observations on the following 3 variables:
WordFormA character vector of word forms (cues).
FrequencyA numeric vector of frequencies.
OutcomesA character vector of meanings (outcomes).
Meanings are separated by underscores. The NIL meaning is ignored.
Baayen, R. H. and Milin, P. and Filipovic Durdevic, D. and Hendrix, P. and Marelli, M., An amorphous model for morphological processing in visual comprehension based on naive discriminative learning. Psychological Review, 118, 438-482.
Baayen, R. H. and Milin, P. and Filipovic Durdevic, D. and Hendrix, P. and Marelli, M., An amorphous model for morphological processing in visual comprehension based on naive discriminative learning. Psychological Review, 118, 438-482.
1 2 3 | data(plurals)
plurals$Cues <- orthoCoding(plurals$WordForm, grams=1)
estimateWeights(cuesOutcomes=plurals)
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