uri(Biodem)
uri()所属R语言包：Biodem
Calculates the Unbiased Random Isonymy matrix
计算无偏的的随机Isonymy矩阵
译者：生物统计家园网 机器人LoveR
描述----------Description----------
"uri" calculates the unbiased random isonymy coefficient starting from surname frequencies.
“URI”计算的无偏的随机isonymy系数从姓的频率开始。
用法----------Usage----------
uri(x)
参数----------Arguments----------
参数：x
is a surname frequency table where the N rows correspond to the surnames present in the whole population and the M columns are the (sub)populations
是一个姓氏的频数分布表中的N行对应于存在于整个人口和M列的姓氏的（子）的人口
Details
详细信息----------Details----------
The function implements Morton's isonymy method as outlined by Relethford. Unbiased estimations of intra-(sub)population isonymy were included. Unbiased Random Isonymy is an argument needed to calculate 'a priori' and conditional kinship matrices using the "rel.phi" and "rel.cond" functions.
该函数实现莫顿的isonymy方法概述Relethford。内（分）人口isonymy的无偏估计。偏的随机Isonymy参数计算所需要的“先验”和有条件的亲属关系矩阵，使用的“rel.phi”和“rel.cond”功能。
值----------Value----------
Returns a square symmetric unbiased isonymy matrix.
返回的方形对称的公正isonymy矩阵。
注意----------Note----------
The use of “uri” could be problematic, because different people are likely to arrange isonymy data in different ways on their computers. We decided for a matrix format for the isonymy data; the function would originally accept data in a different format and then convert it internally, but this would be a problem for people with data arranged in a different format. In the end we decided to write a specific function, "sur.freq", to generate surname frequency tables directly from raw marriage data or marriage-like data (the most commonly used sources in bio-demographic studies). For other types of surname data, see the verbose explanation in the info for the dataset "surnames" so it would be clear for the user how “uri” works.
“URI”的使用是有问题的，因为不同的人有可能以不同的方式在自己的电脑上安排isonymy数据。我们决定矩阵格式的isonymy数据的功能原本接受的数据以不同的格式，然后将其转换内部，但是这将是一个问题的人安排在不同的格式的数据。最后，我们决定写一个特定的功能，“sur.freq”，产生姓频率表，直接从原的婚姻数据或结婚类似的数据（人口生物研究中最常用的来源）。姓氏的数据对于其他类型数据集“姓氏”的信息，请参阅详细的解释，所以这将是明确的用户如何“URI”的作品。
（作者）----------Author(s)----------
Federico C. F. Calboli and Alessio Boattini <a href="mailto:alessio.boattini2@unibo.it">alessio.boattini2@unibo.it</a>
参考文献----------References----------
J. F Crow and C Denniston (eds.). New York, Plenum Press, 97-104. Relethford, J. H. 1988. Estimation of kinship and genetic distance from
参见----------See Also----------
sur.freq to generate the input surname frequency table from marriage data, surnames for an explanation on how to generate the correct input table from other surname sources, lasker for a similar kinship coefficient derived from surnames, hedrick for a standardized kinship coefficient derived from surnames, rri to calculate an unbiased estimate of Regional Random Isonymy from surnmaes rel.phi to calculate an 'a priori' kinship matrix from isonymy data, rel.cond to calculate a conditional kinship matrix from isonymy data
sur.freq产生输入姓氏频率从婚姻数据表，surnames解释如何生成正确的输入表从其他姓氏来源，lasker来自一个类似的亲属关系系数姓氏，hedrick姓氏来源于一个标准化的亲属关系系数，rri来计算的无偏估计从surnmaes区域随机Isonymy的rel.phi计算的“先天的”血缘关系矩阵isonymy数据， rel.cond计算有条件的亲属关系矩阵isonymy数据
实例----------Examples----------
# starting from a raw marriage records dataset:[从原始婚姻记录的数据集：]
data(valley)
tot <- sur.freq(valley,PAR,SURM,SURF)
tot # a frequency table calculated above all the surnames[以上所有的姓氏计算的频率表]
iso.matrix <- uri(tot)
iso.matrix # a unbiased random isonymy matrix[一个公正的任意isonymy矩阵]
#starting from a generic surname frequency table[从一个普通的姓氏频率表]
data(surnames)
surnames # a made-up dataset[一个虚构的数据集]
# you can see that the surnames are arranged as the _rows_[你可以看到，姓氏被作为_rows_布置]
# and the populations are the _columns_[和人口是_columns_的]
# the function "uri" turns this data into a unbiased random isonymy matrix[“URI”的功能，把这个数据转换成一个公正的任意isonymy矩阵]
iso.matrix <- uri(surnames)
iso.matrix
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 2012-9-14 22:35:29
