TraMineR-package(TraMineR)
TraMineR-package()所属R语言包：TraMineR
Trajectory miner: a toolbox for exploring and rendering sequence data
轨迹矿工：一个工具箱，探索和渲染序列数据
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This package is a toolbox for sequence manipulation, description, rendering and more generally the mining of sequence data in the field of social sciences. Though it is primarily intended for analyzing state or event sequences that describe life courses such as family formation histories or professional careers its features also apply to many other kinds of categorical sequence data. It accepts many different sequence representations as input and provides tools for translating sequences from one format to another. It offers several statistical functions for describing and rendering sequences, for computing distances between sequences with different metrics among which optimal matching, the longest common prefix and the longest common subsequence, and simple functions for extracting the most frequent subsequences and identifying the most discriminating ones among them. A user's guide can be found on TraMineR's web page.
该软件包是一个工具箱，用于操作序列，说明，渲染和更普遍的序列数据挖掘在社会科学领域。虽然它的主要目的是描述生活的课程，如家庭形成的历史或职业生涯中的状态或事件序列，分析其功能也适用于许多其他类型的分类序列数据。它接受许多不同的序列表示作为输入，并提供了工具来翻译序列为另一种格式。它提供了多种统计功能描述和渲染序列，计算提取最常见的子序列，并确定最挑剔的之间的不同指标之间的最佳匹配，共同的前缀最长的最长公共子序列，和简单的功能序列之间的距离它们。特拉米纳的网页的用户指南上可以找到。
TraMineR provides tools for both state sequences and event sequences. The first step when using the package is to define a state sequence object (with seqdef) if you want to explore state sequences, and an event sequence object (with seqecreate) if you are interested in event sequencing.
特拉米纳状态序列和事件序列的工具。使用包时的第一步是定义一个状态序列对象（用seqdef），如果你想探索的状态序列，事件序列对象（seqecreate）如果你有兴趣在事件排序。
State sequences are defined from a series of variables giving the states at the successive positions, while event sequences are defined from (vertical) time stamped event data. The package, however, can handle many other different data organizations and provides tools to help converting state sequences into event sequences and vice versa.
状态序列定义的从一系列给的状态在连续的位置上，而事件序列被定义为从（垂直）的时间标记的事件数据的变量。然而，该软件包，可以处理许多其他不同的数据组织和提供的工具来帮助转换到事件序列的状态序列，反之亦然。
Details
详细信息----------Details----------
Index:
指数：
（作者）----------Author(s)----------
Alexis Gabadinho <alexis.gabadinho@unige.ch>, Matthias Studer <matthias.studer@unige.ch>, Nicolas S. M眉ller <nsmuller@gmail.com>, Gilbert Ritschard <gilbert.ritschard@unige.ch> and contributions from Reto B眉rgin <reto.buergin@unige.ch>.
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Maintainer: Gilbert Ritschard <gilbert.ritschard@unige.ch>
参考文献----------References----------
Analyzing and Visualizing State Sequences in R with TraMineR. Journal of Statistical Software 40(4), 1-37.
Mining Sequence Data in <code>R</code> with the <code>TraMineR</code> package: A users guide. Department of Econometrics and Laboratory of Demography, University of Geneva
实例----------Examples----------
## load the mvad data[＃加载MVAD数据]
library(TraMineR)
data(mvad)
## create a state sequence object from columns 17 to 86[＃创建一个状态序列对象列17至86]
mvad.seq <- seqdef(mvad[,17:86])
## distribution plot by sex (male)[按性别分布图（男）]
seqdplot(mvad.seq, group=mvad$male, border=NA)
## compute the LCS pairwise distance matrix[＃计算LCS两两距离矩阵。]
## among the first 10 sequences[＃首批10个序列]
mvad.lcs <- seqdist(mvad.seq[1:10,], method="LCS")
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 2012-10-1 11:42:25
