zipfR-package(zipfR)
zipfR-package()所属R语言包：zipfR
zipfR: lexical statistics in R
在R zipfR：词汇统计
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The zipfR package performs Large-Number-of-Rare-Events (LNRE) modeling of (linguistic) type frequency distributions (Baayen 2001) and provides utilities to run various forms of lexical statistics analysis in R.
zipfR包进行大数量的稀土的活动（LNRE）建模（语言）型频率分布（Baayen 2001年），并提供工具来运行各种形式的词汇统计分析R.
Details
详细信息----------Details----------
The best way to get started with zipfR is to read the tutorial, which you can find via the HTML documentation (follow the Overview link); you can also download it from http://purl.org/stefan.evert/zipfR/
最好的方式开始与zipfR阅读教程，通过HTML文档（按照“概述”链接），你可以找到的，你也可以下载它从http://purl.org/stefan.evert/zipfR/
zipfR is released under the GNU General Public License (http://www.gnu.org/copyleft/gpl.html)
zipfR下发布的GNU通用公共许可证（http://www.gnu.org/copyleft/gpl.html）
（作者）----------Author(s)----------
Stefan Evert <<a href="mailto:stefan.evert@uos.de">stefan.evert@uos.de</a>> and Marco Baroni
<<a href="mailto:marco.baroni@unitn.it">marco.baroni@unitn.it</a>>
Maintainer: Stefan Evert <<a href="mailto:stefan.evert@uos.de">stefan.evert@uos.de</a>>
参考文献----------References----------
Dordrecht.
L眉deling and M. Kyt枚 (eds.), Corpus Linguistics. An International Handbook, chapter 39. Mouton de Gruyter, Berlin.
Pairs and Collocations. PhD Thesis, IMS, University of Stuttgart. URN urn:nbn:de:bsz:93-opus-23714 http://elib.uni-stuttgart.de/opus/volltexte/2005/2371/
sequences. Proceedings of JADT 2004, 411-422.
quality of word frequency models. Proceedings of Corpus Linguistics 2005.
other rare events in R. useR! 2006: The second R user conference.
参见----------See Also----------
The zipfR tutorial: available from http://purl.org/stefan.evert/zipfR/ and via the HTML documentation (by following the Overview link)
zipfR教程：，可从http://purl.org/stefan.evert/zipfR/和通过HTML文件（概述链接）
Some good entry points into the zipfR documentation are be spc, vgc, tfl, read.spc, read.tfl, read.vgc, lnre, lnre.vgc, plot.spc, plot.vgc
有一些很好的入口点到zipfR文档是spc，vgc，tfl，read.spc，read.tfl，read.vgc，lnre ，lnre.vgc，plot.spc，plot.vgc
The same authors also develop the corpora library (available on CRAN) supporting simple inferential statistics for corpus analysis
同一作者还开发了corpora库（CRAN）支持简单的推论统计语料分析
Harald Baayen's LEXSTATS tools: http://www.mpi.nl/world/persons/private/baayen/software.html
哈拉尔Baayen LEXSTATS工具：http://www.mpi.nl/world/persons/private/baayen/software.html
Stefan Evert's UCS tools: http://collocations.de/
斯特凡·埃弗特的UCS工具：http://collocations.de/的
实例----------Examples----------
## load Oliver Twist and Great Expectations frequency spectra[＃负载雾都孤儿“和”远大前程“频谱]
data(DickensOliverTwist.spc)
data(DickensGreatExpectations.spc)
## check sample size and vocabulary and hapax counts[＃检查样本的大小和词汇和hapax的计数]
N(DickensOliverTwist.spc)
V(DickensOliverTwist.spc)
Vm(DickensOliverTwist.spc,1)
N(DickensGreatExpectations.spc)
V(DickensGreatExpectations.spc)
Vm(DickensGreatExpectations.spc,1)
## compute binomially interpolated growth curves[＃计算二项式插值的生长曲线]
ot.vgc <- vgc.interp(DickensOliverTwist.spc,(1:100)*1570)
ge.vgc <- vgc.interp(DickensGreatExpectations.spc,(1:100)*1865)
## plot them[＃图]
plot(ot.vgc,ge.vgc,legend=c("Oliver Twist","Great Expectations"))
## load Dickens' works frequency spectrum[＃加载狄更斯的作品频谱]
data(Dickens.spc)
## compute Zipf-Mandelbrot model from Dickens data[＃计算齐普夫 - 曼德尔布罗从狄更斯数据模型]
## and look at model summary[＃看看模型总结]
zm <- lnre("zm",Dickens.spc)
zm
## plot observed and expected spectrum[观察到的和预期的频谱＃图]
zm.spc <- lnre.spc(zm,N(Dickens.spc))
plot(Dickens.spc,zm.spc)
## obtain expected V and V1 values at arbitrary sample sizes[＃取得预期的V和V1值在任意样本量。]
EV(zm,1e+8)
EVm(zm,1,1e+8)
## generate expected V and V1 growth curves up to a sample size[＃产生预期的V和V1增长的曲线样本大小。]
## of 10 million tokens and plot them, with vertical line at [＃10万元标记，并绘制出来，与垂直线]
## estimation size[＃估计大小]
ext.vgc <- lnre.vgc(zm,(1:100)*1e+5,m.max=1)
plot(ext.vgc,N0=N(zm),add.m=1)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-2 07:51:08
