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R语言 TraMineR包 seqici()函数中文帮助文档(中英文对照)

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发表于 2012-10-1 11:38:58 | 显示全部楼层 |阅读模式
seqici(TraMineR)
seqici()所属R语言包:TraMineR

                                        Complexity index of individual sequences
                                         单个顺序的复杂性指数

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

Computes the complexity index, a composite measure of sequence complexity. The index uses the number of transitions in the sequence as a measure of the complexity induced by the state ordering and the longitudinal entropy as a measure of the complexity induced
计算复杂性指数,综合衡量序列复杂性。索引使用序列中的跃变的次数,作为衡量诱导的状态排序的复杂性和纵向熵作为衡量的复杂诱导


用法----------Usage----------


seqici(seqdata, with.missing=FALSE)



参数----------Arguments----------

参数:seqdata
a sequence object as returned by the the seqdef function.
返回的序列对象的seqdef功能。


参数:with.missing
if set to TRUE, missing status (gaps in sequences) is handled as an additional state when computing the state distribution and the number of transitions in the sequence.
如果设置为TRUE,缺失的现状(序列中的差距)的处理计算时的状态分布和数量的转换序列中的一个额外的状态。


Details

详细信息----------Details----------

The complexity index C(s) of a sequence s is
的复杂性指数C(s)的序列s

where q(s) is the number of transitions in the sequence,  q_{max} the maximum number of transitions,   h(s) the within entropy, and h_{max} the theoretical maximum  entropy which is h_max = -log 1/|A|.
其中q(s)是序列中的转换次数,q_{max}的最大数量的转换,h(s)内的熵,和h_{max}最大熵理论,这是<X >。

The index C(s) is the geometric mean of its two components which are normalized. The minimum value of 0 can only be reached by a sequence made of one distinct state, containing thus 0 transitions and having an entropy of 0. The maximum 1 of C(s) is reached when the two following conditions are fulfilled: i) Each of the state in the alphabet is present in the sequence and the total durations are uniform, that is, equal to l/a and ii) The number of transitions in the sequence is equal to l-1, that is, the length l_d of the DSS is equal to the length of the sequence l
指数C(s)是它的两个组件,这些组件标准化的几何平均值。只能达到最小值0的序列由一个不同的状态,因此,包含0的跳变,并具有0的熵。最大的1C(s)达到以下两个条件都满足时,I)的状态在字母表中的每一个序列中,总的持续时间是一致的,那就是等于l/a和ii)在序列中的转换次数等于l-1,即,长度l_d的DSS是等于序列长度l的


值----------Value----------

a vector of length equal to the number of sequences in seqdata containing the complexity index value of each sequence.
的向量长度的序列的数量等于seqdata含有每个序列的复杂性指数值。


(作者)----------Author(s)----------


Alexis Gabadinho



参考文献----------References----------


N.S. (2010). "Indice de complexit茅 pour le tri et la comparaison de s茅quences cat茅gorielles", In Extraction et gestion des connaissances (EGC 2010), Revue des nouvelles technologies de

参见----------See Also----------

seqient, seqST
seqient,seqST


实例----------Examples----------


## Creating a sequence object from the mvad data set[#创建一个序列对象MVAD数据集]
data(mvad)
mvad.labels <- c("employment", "further education", "higher education",
                    "joblessness", "school", "training")
mvad.scodes <- c("EM","FE","HE","JL","SC","TR")
mvad.seq <- seqdef(mvad, 15:86, states=mvad.scodes, labels=mvad.labels)

##[#]
mvad.ci <- seqici(mvad.seq)
summary(mvad.ci)
hist(mvad.ci)

## Example using with.missing argument[#示例使用with.missing参数]
data(ex1)
ex1.seq <- seqdef(ex1, 1:13)
seqici(ex1.seq)
seqici(ex1.seq, with.missing=TRUE)

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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