vim.permSNP(logicFS)
vim.permSNP()所属R语言包：logicFS
Permutation Based Importance Measures
排列为基础的重要性措施
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes the importances of input variables, SNPs, or sets of SNPs, respectively, based on permutations of the response. Currently only available for the classification and the logistic regression approach of logic regression.
计算输入变量的重要性，单核苷酸多态性，或单核苷酸多态性集，分别基于排列的响应。目前仅可用于分类和逻辑回归Logistic回归方法。
用法----------Usage----------
vim.permInput(object, n.perm = NULL, standardize = TRUE,
rebuild = FALSE, prob.case = 0.5, useAll = FALSE, version = 1,
adjust = "bonferroni", addMatPerm = FALSE, rand=NA)
vim.permSNP(object, n.perm = NULL, standardize = TRUE,
rebuild = FALSE, prob.case = 0.5, useAll = FALSE, version = 1,
adjust = "bonferroni", addMatPerm = FALSE, rand = NA)
vim.permSet(object, set = NULL, n.perm = NULL, standardize = TRUE,
rebuild = FALSE, prob.case = 0.5, useAll = FALSE, version = 1,
adjust = "bonferroni", addMatPerm = FALSE, rand = NA)
参数----------Arguments----------
参数：object
an object of class logicBagg, i.e.\ the output of logic.bagging.
一个类对象logicBagg，即\logic.bagging的输出。
参数：set
either a list or a character or numeric vector. If NULL (default), then it will be assumed that data, i.e.\ the data set used in the application of logic.bagging, has been generated using make.snp.dummy or similar functions for coding variables by binary variables, i.e.\ with a function that splits a variable, say SNPx, into the dummy variables SNPx.1, SNPx.2, ... (where the “." can also be any other sign, e.g., an underscore). If a character or a numeric vector, then the length of set must be equal to the number of variables used in object, i.e.\ the number of columns of data in the logicBagg object, and must specify the set to which a variable belongs either by an integer between 1 and the number of sets, or by a set name. If a variable should not be included in any of the sets, set the corresponding entry of set to NA. Using this specification of set it is not possible to assign a variable to more than one sets. For such a case, set set to a list (as follows). If set is a list, then each object in this list represents a set of variables. Therefore, each object must be either a character or a numeric vector specifying either the names of the variables that belongs to the respective set or the columns of data that contains these variables. If names(set) is NULL, generic names will be employed as names for the sets. Otherwise, names(set) are used.
一个列表或一个字符或数字向量。 NULL如果（默认），然后将假定data，即\中的应用使用数据集logic.bagging，已产生使用make.snp.dummy或类似功能编码二进制变量的变量，即\分割变量与函数，说成假人的变量SNPx.1，SNPx.2 SNPX，... （“。”也可以是任何其他标志，如下划线）。如果一个字符或数字向量，然后的set长度必须等于object，即\列数data<X中使用的变量的数量>对象，必须指定一个变量属于1套，之间的整数，或由一个集名称的集合。如果一个变量不应包括在任何套，设置相应的条目logicBaggset。使用本规范NA这是不可能指定一个变量多套。对于这样的情况下，设置一个列表set（如下）。如果set是一个列表，然后在此列表中的每个对象代表一组变量。因此，每个对象必须是一个字符或一个数值向量指定的变量属于各自的组或列的名称set包含这些变量。如果datanames(set)，通用名称将受聘为集的名称。否则，NULL使用。
参数：n.perm
number of permutations used in the computation of the importances. By default (i.e.\ if n.perm = NULL), 100 permutations are used if rebuild = TRUE and the regression approach of logic regression has been used in logic.bagging (by setting ntrees to an integer larger than 1, or glm.if.1tree = TRUE). Otherwise, 1000 permutation are employed. Note that actually much more permutations should be used.
数计算的重要性排列。默认情况下（即\如果n.perm = NULL），100排列如果rebuild = TRUE“逻辑回归的回归方法已在logic.bagging（用于设置ntrees整数大于1，或glm.if.1tree = TRUE）。否则，1000置换就业。请注意，实际上多的排列，应使用。
参数：standardize
should the standardized importance measure be used?
应该使用标准化的重要性措施？
参数：rebuild
logical indicating whether the logic regression models should be rebuild (i.e.\ the parameters beta of the generalized linear models should be recomputed) after removing a variable or a set of variables from the logic trees and for each permutation of the response. Note that setting rebuild = TRUE increases the computation time substantially.
逻辑表示逻辑回归模型是否应该重建（即\参数beta广义线性模型应重新计算）后，从逻辑树删除一个变量或一组变量和每个置换响应。请注意，设置rebuild = TRUE计算时间大幅增加。
参数：prob.case
a numeric value between 0 and 1. If the logistic regression approach of logic regression has been used in logic.bagging, then an observation will be classified as a case (or more exactly, as 1), if the class probability of this observation is larger than prob.case. Otherwise, prob.case is ignored.
0和1之间的数值。如果使用逻辑回归Logistic回归方法已在logic.bagging，然后观察将被列为情况（或者更确切地说，为1），如果这个观察类的概率比prob.case 。否则，prob.case被忽略。
参数：useAll
logical indicating whether all m * n.perm permuted values should be used in the computation of the permutation based p-values, where m is the number of variables or sets of variables, respectively. If FALSE, the n.perm permuted values corresponding to the respective variable (or set of variables) are employed in the determination of the p-value of this variable (or set of variables).
逻辑表示，是否所有的m *n.perm置换值应在置换p值的计算，其中m是变量或组变量的数目，分别。如果FALSE，n.perm置换值对应到各自的变量（或变量）受聘在确定这个变量的p值（或变量）。
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.
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。
参数：addMatPerm
should the (n.perm + 1) x m matrix containing the original values (first column) and the permuted values (the remaining columns) of the importance measure for the m variables or m sets of variables be added to the output?
应（n.perm+ 1）Xm矩阵包含m变量或原始值（第一列）和置换价值的重要措施（其余列）m添加到输出变量的套？
参数：rand
an integer for setting the random number generator in a reproducible state.
重现状态设置随机数发生器的整数。
值----------Value----------
An object of class logicFS containing
一个类的对象logicFS含有
参数：vim
the values of the importance measure for the input variables, the SNPs, or the sets of SNPs, respectively,
输入变量，单核苷酸多态性，或单核苷酸多态性，分别套价值的重要措施，
参数：prop
NULL,
NULL
参数：primes
the names of the inputs, SNPs, or sets of variables, respectively,
输入，单核苷酸多态性，或变量集，分别名，
参数：type
the type of model (1: classification, 3: logistic regression),
类型（1：分类，3：logistic回归）模型，
参数：param
NULL,
NULL
参数：mat.imp
NULL,
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：threshold
0.95, i.e.\ the suggested threshold for calling an input, SNP or set of SNPs, respectively, important (this is just used as default value when plotting the importances, see argument thres of plot.logicFS),
0.95，即\调用输入，SNP或设置的SNPs，分别，重要的建议阈值（这只是策划的重要性时，使用默认值，请参阅参数thresplot.logicFS）
参数：mu
NULL,
NULL
参数：useN
TRUE,
TRUE
参数：name
either "Variable", "SNP", or "Set",
要么"Variable"，"SNP"或"Set"
参数：mat.perm
if addMatPerm = FALSE, NULL; otherwise, a matrix containing the original and the permuted values of the respective importance measure.
如果addMatPerm = FALSE，NULL;否则，一个矩阵包含原始和置换值各自的重要性措施。
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, vim.input, vim.set, vim.signperm
logic.bagging，vim.input，vim.set，vim.signperm
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。
|
发表于 2012-2-25 23:36:26
