vim.norm(logicFS)
vim.norm()所属R语言包：logicFS
Standardized and Sign-Permutation Based Importance Measure
标准化和基于符号排列重要性度量
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes a standarized or a sign-permutation based version of either the Single Tree Measure, the Quantitative Response Measure, or the Multiple Tree Measure.
计算标化或排列的单一树种的测量，定量的应对措施，或多重树测量标志的版本。
用法----------Usage----------
vim.norm(object, mu = 0)
vim.signperm(object, mu = 0, n.perm = 10000, n.subset = 1000,
version = 1, adjust = "bonferroni", rand = NA)
参数----------Arguments----------
参数：object
either the output of logicFS or vim.logicFS with addMatImp = TRUE, or the output of logic.bagging with importance = TRUE and addMatImp = TRUE.
无论是输出logicFS或vim.logicFSaddMatImp = TRUE，或输出logic.baggingimportance = TRUE和addMatImp = TRUE。
参数：mu
a non-negative numeric value against which the importances are tested. See Details.
一个非负的数值，对测试的重要性。看到Details。
参数：n.perm
the number of sign permutations used in vim.signperm.
vim.signperm使用的符号排列。
参数：n.subset
an integer specifying how many permutations should be considered at once.
一个整数，指定多少排列，应被视为一次。
参数：version
either 1 or 2. If 1, then the importance measure is computed by 1 - padj, where padj is the adjusted p-value. If 2, the importance measure is determined by -log10(padj), where a raw p-value equal to 0 is set to 1 / (10 * n.perm) to avoid infinitive importances.
无论是1或2。如果1，那么的重要措施是由1 - padj计算，其中padj是调整p值。如果2“的重要措施被确定通过的LOG10（padj）的，在原始的p值等于0设置为1 /（10 *n.perm），以避免不定式的重要性。
参数：adjust
character vector naming the method with which the raw permutation based p-values are adjusted for multiplicity. If "qvalue", the function qvalue.cal from the package siggenes is used to compute q-values. Otherwise, p.adjust is used to adjust for multiple comparisons. See p.adjust for all other possible specifications of adjust. If "none", the raw p-values will be used. For more details, see Details.
特征向量命名原始置换的p值与多重调整的方法。如果"qvalue"，功能qvalue.cal从包siggenes用于计算Q值。否则，p.adjust是用来调整多重比较。看到p.adjust所有adjust的其他可能的规格。如果"none"，原材料的P-值将用于。有关详细信息，请参阅Details。
参数：rand
an integer for setting the random number generator in a reproducible case.
设置在一个可重复的情况下随机数发生器的整数。
Details
详情----------Details----------
In both vim.norm and vim.signperm, a paired t-statistic is computed for each prime implicant, where the numerator is given by VIM - mu with VIM being the single or the multiple tree importance, and the denominator is the corresponding standard error computed by employing the B improvements of the considered prime implicant in the B logic regression models, where VIM is the mean over these B improvements.
在这两个vim.norm和vim.signperm，配对t-统计量的计算，其中分子是由每个黄金蕴含VIM - mu用Vim的单个或多个树的重要性，分母是相应的标准由用人B改进所考虑的首要蕴含B逻辑回归模型，Vim在哪里是这些B改善，平均计算的错误。
Note that in the case of a quantitative response, such a standardization is not necessary. Thus, vim.norm returns a warning when the response is quantitative, and vim.signperm does not divide VIM - mu by its sample standard error.
请注意，在一个定量反应的情况下，这样的标准化是没有必要的。因此，vim.norm返回一个警告的反应是定量时，与vim.signperm不分裂VIM - mu其样本的标准误差。
Using mu = 0 might lead to calling a prime implicant important, even though it actually shows only improvements of 1 or 0. When considering the prime implicants, it might be therefore be helpful to set mu to a value slightly larger than zero.
使用mu = 0可能导致调用素蕴含重要，即使它实际上只提高0或1。当考虑首要implicants，它可能因此成为有用设置mu稍大大于零的值的。
In vim.norm, the value of this t-statistic is returned as the standardized importance of a prime implicant. The larger this value, the more important is the prime implicant. (This applies to all importance measures – at least for those contained in this package.) Assuming normality, a possible threshold for a prime implicant to be considered as important is the 1 - 0.05 / m quantile of the t-distribution with B - 1 degrees of freedom, where m is the number of prime implicants.
在vim.norm，这个t-统计的返回值作为一个主要蕴含标准化的重要性。该值越大，更重要的是首要的蕴涵。 （这适用于所有的重要性措施 - 至少在这个包中包含的那些）。假设常态，可能作为重要考虑的一个主要蕴含阈值<1 - 0.05 / mt分布的分位数X>自由度，其中B - 1素implicants的数量。
In vim.signperm, the sign permutation is used to determine n.perm permuted values of the one-sample t-statistic, and to compute the raw p-values for each of the prime implicants. Afterwards, these p-values are adjusted for multiple comparisons using the method specified by adjust. The permutation based importance of a prime implicant is then given by 1 - these adjusted p-values. Here, a possible threshold for calling a prime implicant important is 0.95.
在vim.signperm，符号置换用于确定n.perm置换的一个样本的t-统计值，并计算每个首要implicants的原料p值。随后，这些P-值调整多个使用adjust指定的方法的比较。素蕴含的排列为基础的重要性，然后由1 -这些调整后的P-值。在这里，调用首要蕴含重要的可能阈值是0.95。
值----------Value----------
An object of class logicFS containing
一个类的对象logicFS含有
参数：primes
the prime implicants,
首要implicants，
参数：vim
the respective importance of the prime implicants,
各自的的首要implicants的重要性，
参数：prop
NULL,
为NULL，
参数：type
the type of model (1: classification, 2: linear regression, 3: logistic regression),
类型分类（1：2：线性回归，logistic回归）模型，
参数：param
further parameters (if addInfo = TRUE),
更多的参数（如果addInfo = TRUE）
参数：mat.imp
NULL,
为NULL，
参数：measure
the name of the used importance measure,
所使用的重要性措施的名称，
参数：useN
the value of useN from the original analysis with, e.g., logicFS,
useN从原来的分析，例如，logicFS的价值，
参数：threshold
the threshold suggested in Details,
阈值建议在Details
参数：mu
mu.
mu。
作者（S）----------Author(s)----------
Holger Schwender, <a href="mailto:holger.schwender@udo.edu">holger.schwender@udo.edu</a>
参考文献----------References----------
Biostatistics, 12, 18-32.
参见----------See Also----------
logic.bagging, logicFS, vim.logicFS, vim.chisq, vim.ebam
logic.bagging，logicFS，vim.logicFS，vim.chisq，vim.ebam
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。
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发表于 2012-2-25 23:36:16
