rriskDistributions(rriskDistributions)
rriskDistributions()所属R语言包：rriskDistributions
Fitting distributions to given data or known quantiles
配件分派给定的数据或已知的位数
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This packages provides a collection of functions for estimation parameters of continuous or discrete distributions (related to the rrisk project) to given data or to known quantiles.
这个包提供了一组连续或离散分布的估计参数的功能（有关的rrisk项目）提供的数据，或为已知位数。
Details
详细信息----------Details----------
This package is a part of the rrisk project and contains functions for fitting distributions to given data or by known quantiles. This package does not depend on the whole rrisk project and can be used separately. The rrisk project can be downloaded from http://www.bfr.bund.de/cd/52158. <br> <br> The main functions fit.perc and fit.cont call a GUI that allows users to choose an appropriate distribution family to given data or to known quantiles without any knowledge of the <acronym>R</acronym> syntax.
这个包是rrisk项目的一部分，其中包含给定数据拟合分布函数或由知名位数。这个包不依赖于整个rrisk项目，可以单独使用。 rrisk项目可以下载从http://www.bfr.bund.de/cd/52158。参考参考的主要功能fit.perc和fit.cont所谓的图形用户界面，允许用户选择一个适当的分配给定的数据或没有任何的<acronym>的知识为已知位数的家庭<X > </首字母缩写语法。
注意----------Note----------
Fitting by given quantiles: a typical application is the definition of a distribution based on expert opinion on some quantiles (e.g., the 2.5th, median and 97.5th) of the trial to be modelled. rrisk has a functionality, to fit all continuous or discrete distributions simultaneously without urging the user to specify the distribution family in advance.
装修由给定位数：一个典型的应用是一个基于专家的意见，在某些位数（例如，2.5次，中位数和97.5th的的）的审判进行建模的定义。 rrisk有一个功能，适合所有连续或离散分布，同时不要求用户指定的分布族提前。
（作者）----------Author(s)----------
Natalia Belgorodski <a href="mailto:belgorodski@stat-up.de">belgorodski@stat-up.de</a>
(<acronym><span class="acronym">STAT-UP</span></acronym> Statistical Consulting), <br> Matthias
Greiner <a href="mailto:matthias.greiner@bfr.bund.de">matthias.greiner@bfr.bund.de</a> (Federal
Institute for Risk Assessment, Germany), <br> Kristin
Tolksdorf <a href="mailto:kristin.tolksdorf@bfr.bund.de">kristin.tolksdorf@bfr.bund.de</a> (Federal
Institute for Risk Assessment, Germany), <br> Katharina
Schueller <a href="mailto:schueller@stat-up.de">schueller@stat-up.de</a> (<acronym><span class="acronym">STAT-UP</span></acronym>
Statistical Consulting)
实例----------Examples----------
q<-qweibull(p=c(0.025,0.5,0.975),shape=2,scale=3)
get.weibull.par(q=q)
q<-qweibull(p=c(0.025,0.5,0.975),shape=0.01,scale=1)
get.weibull.par(q=q)
res.fitcont<-fit.cont(data2fit=rnorm(100))
res.fitcont
res.fitperc<-fit.perc()
res.fitperc
p=c(0.025,0.50,0.975)
q=c(9.68,29.2,50.98)
fit.results<-rriskFitdist.perc(p,q,show.output=FALSE)
plotDiagnostics.perc(fit.results)
p=c(0.25,0.50,0.75)
q=c(9.68,29.2,50.98)
fit.results<-rriskFitdist.perc(p,q,show.output=FALSE)
plotDiagnostics.perc(fit.results)
plotDiagnostics.perc(fit.results,tolPlot=2)
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 2012-9-28 21:13:12
