confIntGPS-methods(Rtreemix)
confIntGPS-methods()所属R语言包：Rtreemix
Method for calculating GPS values and their 95% bootstrap
GPS的价值观和他们95％的bootstrap计算方法
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The method first calculates the genetic progression score (GPS) for the patterns in a given dataset data based on a fitted mutagenetic trees mixture model with K components. The data and K have to be specified. Then, it derives a 95% confidence intervals for the GPS values with bootstrap analysis.
该方法首先计算出在给定的数据集的遗传进展的得分模式（GPS）的dataK组件装致突变树木混合模型。 data和K必须指定。然后，它源于一个全球定位系统引导分析值的95％置信区间。
用法----------Usage----------
confIntGPS(data, K, ...)
参数----------Arguments----------
参数：data
An RtreemixData object containing the samples (patterns of genetic events) for which the GPS values and their bootstrap confidence intervals are to be calculated. The number of genetic events should NOT be greater than 20.
RtreemixData对象，其中包含GPS的价值观和他们的引导置信区间来计算的样本（基因活动模式）。遗传事件的数量不宜大于20。
参数：K
An integer larger than 0 specifying the number of branchings in the mixture model.
integer大于0指定的分枝的混合模型。
参数：...
sampling.mode is a character that specifies the sampling mode ("constant" or "exponential") used in the waiting time simulations. Its default value is "exponential". sampling.param is a numeric that specifies the sampling parameter corresponding to the sampling mode given by sampling.mode. Its default value is 1. no.sim is an integer larger than 0 giving the number of iterations for the waiting time simulation. Its default values is 10000. B is an integer larger than 0 specifying the number of bootstrap samples used in the bootstrap analysis. Its default value is 1000. equal.star is a logical specifying whether to use equal edge weights in the noise component. The default value is TRUE. When you have few data samples always use its default value (TRUE) to ensure nonzero probabilities for all possible patterns (sets of events).
sampling.mode是character指定的等待时间模拟中使用的采样模式（“不变”或“指数”）。其默认值是“指数”。 sampling.param是numeric指定sampling.mode采样模式给予相应的采样参数。其默认值是1。 no.sim是integer大于0等待时间模拟的迭代次数。它的默认值是10000。 B是integer大于0指定引导在引导分析样品的数量。其默认值是1000。 equal.star是logical指定是否使用噪声分量相等的边权重。默认值是TRUE。当你有几个数据样本始终使用其默认值（TRUE），以确保所有可能的模式（事件集）非零概率。
值----------Value----------
The function returns an object from the RtreemixGPS class that containes the calculated GPS values, their 95% confidence intervals, the model used for the computation, the data, and so on (see RtreemixGPS-class). The GPS values are represented as a numeric vector with length equal to the number of samples in data. Their corresponding confidence intervals are given in a matrix with two columns.
该函数返回的RtreemixGPS类中包含与全球定位系统的计算值，其95％置信区间，用于计算，数据模型的对象，等等（见RtreemixGPS-class）。 GPS值代表一个numeric向量长度等于样品data的数量。其相应的置信区间矩阵中的两列。
注意----------Note----------
The data for which the GPS values and their corresponding confidence intervals are to be calculated should not have more than 20 genetic events. The reason for this is that the number of all possible patterns for which the GPS values are calculated during a computationally intensive simulations is in this case $2^20$. This demands too much memory. The GPS examples are time consuming. They are commented out because of the time restrictions of the check of the package. For trying out the code please copy it and uncomment it.
GPS价值观和其相应的置信区间是要计算的数据不应该有超过20个遗传事件。这样做的原因是，所有可能的模式为GPS值计算期间计算密集型模拟的数量是在这种情况下$ 2 ^ 20元。这需要太多的记忆。 GPS的例子是费时。他们注释掉，因为包检查的时间限制。试图代码请复制并取消它。
作者（S）----------Author(s)----------
Jasmina Bogojeska
参见----------See Also----------
RtreemixGPS-class, gps-methods, RtreemixData-class, RtreemixModel-class, fit-methods
RtreemixGPS-class，gps-methods，RtreemixData-class，RtreemixModel-class，fit-methods
举例----------Examples----------
## Create an RtreemixData object from a randomly generated RtreemixModel object.[＃创建一个RtreemixData对象从随机产生RtreemixModel对象。]
#rand.mod <- generate(K = 2, no.events = 7, noise.tree = TRUE, prob = c(0.2, 0.8))[rand.mod < - 生成（k = 2，no.events = 7，noise.tree = TRUE，概率= C（0.2，0.8））]
#data <- sim(model = rand.mod, no.draws = 400)[数据< - SIM卡（型号= rand.mod，no.draws = 400）]
## Create an RtreemixGPS object by calculating GPS values for a given dataset[＃创建一个给定的数据集GPS值计算RtreemixGPS对象]
## and their 95% confidence intervals using the bootstrap method.[＃和95％置信区间，使用引导方法。]
#modGPS2 <- confIntGPS(data = data, K = 2, B = 100) ## time consuming computation[modGPS2 < - confIntGPS（数据=数据，钾= 2，乙= 100）＃耗时计算]
#show(modGPS2)[展（modGPS2）]
## See the GPS values for the object modGPS2 and their confidence intervals.[＃见的的对象modGPS2和置信区间的GPS值。]
#GPS(modGPS2)[GPS（modGPS2）]
#gpsCI(modGPS2)[gpsCI（modGPS2）]
## See data.[＃查看数据。]
#getData(modGPS2)[的getData（modGPS2）]
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 2012-2-26 13:42:07
