milk(robustbase)
milk()所属R语言包:robustbase
Daudin's Milk Composition Data
Daudin的牛奶成分数据
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Daudin et al.(1988) give 8 readings on the composition of 86 containers of milk. They speak about 85 observations, but this can be explained with the fact that observations 63 and 64 are identical (as noted by Rocke (1996)).
daudin等人(1988)给出的86的牛奶的容器的组合物上的8个读数。他们讲约85观测的,但是,这可以解释观测63和64是相同的(如Rocke(1996)指出的)的事实。
The data set was used for analysing the stability of principal component analysis by the bootstrap method. In the same context, but using high breakdown point robust PCA, these data were analysed by Todorov et al.(1994). Atkinson (1994) used these data for ilustration of the forward search algorithm for identifying of multiple outliers.
该数据集用于主成分分析的引导方法的稳定性分析。在同样的背景,但使用高击穿点鲁棒PCA,托多罗夫等人(1994年)这些数据进行了分析。阿特金森(1994)利用这些数据ilustration向前搜索算法识别多个离群。
用法----------Usage----------
data(milk)
格式----------Format----------
A data frame with 86 observations on the following 8 variables, all but the first measure units in grams / liter.
86以下8个变量的观测的数据框,所有单位克/升的第一项措施。
X1 density
X1密度
X2 fat content
X2脂肪含量
X3 protein content
X3蛋白质含量
X4 casein content
X4酪蛋白含量
X5 cheese dry substance measured in the factory
X5奶酪测量的干燥物质在工厂
X6 cheese dry substance measured in the laboratory
X6奶酪在实验室中测量的干燥物质
X7 milk dry substance
X7牛奶干物质
X8 cheese product
X8奶酪产品
源----------Source----------
Daudin, J.J. Duby, C. and Trecourt, P. (1988) Stability of Principal Component Analysis Studied by the Bootstrap Method; Statistics 19, 241–258.
Daudin,J.J. P.(1988)迪比,C.和Trecourt的的,稳定的主成分分析的Bootstrap方法研究,统计,19,241-258。
参考文献----------References----------
Stability of High Breakdown Point Robust PCA, in Short Communications, COMPSTAT'94; Physica Verlag, Heidelberg.
Fast Very Robust Methods for the Detection of Multiple Outliers. J. Amer. Statist. Assoc. 89 1329–1339.
Identification of Outliers in Multivariate Data; J. Amer. Statist. Assoc. 91 (435), 1047–1061.
实例----------Examples----------
data(milk)
covMcd(milk)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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