auxiliaries: Auxiliaries for regular and irregular verbs in Dutch
In languageR: Analyzing Linguistic Data: A Practical Introduction to Statistics
Description
Usage
Format
References
Examples
Description
For 285 regular and irregular Dutch verbs, the auxiliary for the present
and past perfect is listed together with the count
of verbal synsets in WordNet. Regular and irregular verbs are matched
in the mean for lemma frequency.
Usage
1
Format
A data frame with 285 observations on the following 4 variables.
Verba factor with 285 monomorphemic Dutch verbs.
Auxa factor with as levels the auxiliaries hebben,
zijn and zijnheb (for verbs allowing both auxiliaries).
VerbalSynsetsa numeric vector witth the number of
verbal synonym sets in WordNet in which the verb is listed.
Regularitya factor with levels irregular and
regular.
References
Baayen, R. H. and Moscoso del Prado Martin, F. (2005)
Semantic density and past-tense formation in three Germanic
languages, Language, 81, 666-698.
Examples
1
2
data(auxiliaries)
kruskal.test(auxiliaries$VerbalSynsets, auxiliaries$Aux)
Example output
Kruskal-Wallis rank sum test
data: auxiliaries$VerbalSynsets and auxiliaries$Aux
Kruskal-Wallis chi-squared = 11.721, df = 2, p-value = 0.00285
languageR documentation built on May 2, 2019, 10:02 a.m.
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Description Usage Format References Examples
Description
For 285 regular and irregular Dutch verbs, the auxiliary for the present and past perfect is listed together with the count of verbal synsets in WordNet. Regular and irregular verbs are matched in the mean for lemma frequency.
Usage
1 |
Format
A data frame with 285 observations on the following 4 variables.
Verba factor with 285 monomorphemic Dutch verbs.
Auxa factor with as levels the auxiliaries
hebben,zijnandzijnheb(for verbs allowing both auxiliaries).VerbalSynsetsa numeric vector witth the number of verbal synonym sets in WordNet in which the verb is listed.
Regularitya factor with levels
irregularandregular.
References
Baayen, R. H. and Moscoso del Prado Martin, F. (2005) Semantic density and past-tense formation in three Germanic languages, Language, 81, 666-698.
Examples
1 2 | data(auxiliaries)
kruskal.test(auxiliaries$VerbalSynsets, auxiliaries$Aux)
|
Example output
Kruskal-Wallis rank sum test
data: auxiliaries$VerbalSynsets and auxiliaries$Aux
Kruskal-Wallis chi-squared = 11.721, df = 2, p-value = 0.00285
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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