addNoise(sdcMicro)
addNoise()所属R语言包：sdcMicro
Adding noise for the perturbation of data
添加数据的扰动噪声
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Various adding noise methods for the perturbation of continuous scaled variables can be used.
连续规模变量的扰动增加噪声的方法都可以使用。
用法----------Usage----------
addNoise(x, noise = 150, method = "additive", p = 0.001, delta=0.1)
参数----------Arguments----------
参数：x
data frame or matrix which should be perturbed
数据框或矩阵扰动
参数：noise
amount of noise (in percentages)
的噪音量（百分比）
参数：method
choose between "additive", "correlated", "correlated2", "restr", "ROMM", "outdect"
选择“添加剂”，“相关”，“correlated2，restr”，“罗姆”，outdect
参数：p
multiplication factor for method "ROMM"
乘法因子法“罗姆”
参数：delta
parameter for method "correlated2", details can be found in the reference below.
参数方法“correlated2，详情可在下面的参考。
Details
详细信息----------Details----------
Method "additive" adds noise completely at random to each variable depending on there size and standard deviation. "correlated" and method "correlated2" adds noise and preserves the covariances as descriped in R. Brand (2001) or in the reference given below. Method "restr" takes the sample size into account when adding noise. Method "ROMM" is an implementation of the algorithm ROMM (Random Orthogonalized Matrix Masking) (Fienberg, 2004). Method "outdect" adds noise only to outliers. The outliers are idedentified with univariate and robust multivariate procedures based on a robust mahalanobis distancs calculated by the MCD estimator.
方法添加剂将噪音完全随机的每个变量有大小和标准差。 “相关”和的方法correlated2添加噪声和保留的协方差作为descriped的R.品牌（2001）或在下面给出的参考。方法“restr”需要的样本量时，考虑增加噪声。方法罗姆是一个执行的算法罗姆（随机正交化矩阵掩蔽）（Fienberg，2004年）。方法“outdect”只离群的噪音。的的离群值idedentified一个强大的的马氏distancs计算的MCD估计的基础上与单因素和强大的多变量程序。
值----------Value----------
An object of class “micro” with following entities:
“微型”类的一个对象，具有以下实体：
参数：x
the original data
的原始数据
参数：xm
the modified (perturbed) data
修改后的数据（扰动）
参数：method
method used for perturbation
方法用于扰动
参数：noise
amount of noise
的噪声量
（作者）----------Author(s)----------
Matthias Templ
参考文献----------References----------
“On the security of noise addition for privacy in statistical databases”, Lecture Notes in Computer Science, vol. 3050, pp. 149-161, 2004. ISSN 0302-9743. Vol. Privacy in Statistical Databases, eds. J. Domingo-Ferrer and V. Torra, Berlin: Springer-Verlag. http://vneumann.etse.urv.es/publications/sci/lncs3050OntheSec.pdf,
Joint UNECE/Eurostat work session on statistical data confidentiality, Geneva, Switzerland, 2005, http://www.niss.org/dgii/TR/wp.11.e(ROMM).pdf
“Random orthogonal matrix masking methodology for microdata release”, International Journal of Information and Computer Security, vol. 2, pp. 86-105, 2008.
Robustification of Microdata Masking Methods and the Comparison with Existing Methods, Lecture Notes in Computer Science, Privacy in Statistical Databases, vol. 5262, pp. 177-189, 2008.
New Developments in Statistical Disclosure Control and Imputation: Robust Statistics Applied to Official Statistics, Suedwestdeutscher Verlag fuer Hochschulschriften, 2009, ISBN: 3838108280, 264 pages.
Practical Applications in Statistical Disclosure Control Using R, Privacy and Anonymity in Information Management Systems New Techniques for New Practical Problems, Springer, 31-62, 2010, ISBN: 978-1-84996-237-7.
参见----------See Also----------
summary.micro
summary.micro
实例----------Examples----------
data(Tarragona)
a1 <- addNoise(Tarragona)
a1
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 2012-9-29 23:16:49
