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:
WordForm
A character vector of word forms (cues).
Frequency
A numeric vector of frequencies.
Outcomes
A 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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