LdaPP-class(rrcov)
LdaPP-class()所属R语言包：rrcov
Class "LdaPP" - Robust method for Linear Discriminant Analysis by Projection-pursuit
“LdaPP类” - 坚固的线性判别分析方法的投影追求
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The class LdaPP represents an algorithms for robust linear discriminant analysis by projection-pursuit approach. The objects of class LdaPP contain the results of the robust linear discriminant analysis by projection-pursuit approach.
类LdaPP表示投影追求的方式为强大的线性判别分析算法。类的对象LdaPP包含投影追求方法的鲁棒线性判别分析的结果。
类对象----------Objects from the Class----------
Objects can be created by calls of the form new("LdaPP", ...) but the usual way of creating LdaPP objects is a call to the function LdaPP which serves as a constructor.
可以通过检测的形式new("LdaPP", ...)“可是通常的方式创建”LdaPP对象是LdaPP作为构造函数的功能调用创建的对象。
插槽----------Slots----------
call: The (matched) function call.
call：（匹配）函数调用。
prior: Prior probabilities used, default to group proportions
prior：先验概率，默认组的比例
counts: number of observations in each class
counts：在每类若干意见
center: the group means
center：本组指
cov: the common covariance matrix
cov：常见的协方差矩阵
raw.ldf: a matrix containing the raw linear discriminant functions - see Details in LdaPP
raw.ldf：包含原始的线性判别函数矩阵 - LdaPP详细
raw.ldfconst: a vector containing the raw constants of each raw linear discriminant function - see Details in LdaPP
raw.ldfconst：一个向量的每种原料的线性判别函数的原始常数 - 看到LdaPP的详细信息
ldf: a matrix containing the linear discriminant functions
ldf：矩阵的线性判别函数
ldfconst: a vector containing the constants of each linear discriminant function
ldfconst：一个向量，包含的每个线性判别函数的常数
method: a character string giving the estimation method used
method：使用一个字符的字符串，给出的估算方法
X: the training data set (same as the input parameter x of the constructor function)
X：训练数据集（相同的构造函数的输入参数x）
grp: grouping variable: a factor specifying the class for each observation.
grp：分组变量：指定一个类为每个观测的一个因素。
扩展----------Extends----------
Class "LdaRobust", directly. Class "Lda", by class "LdaRobust", distance 2.
类"LdaRobust"，直接。类"Lda"，类的“LdaRobust”，距离2。
方法----------Methods----------
predict signature(object = "LdaPP"): calculates prediction using the results in object. An optional data frame or matrix in which to look for variables with which to predict. If omitted, the training data set is used. If the original fit used a formula or a data frame or a matrix with column names, newdata must contain columns with the same names. Otherwise it must contain the same number of columns, to be used in the same order. If the argument raw=TRUE is set the raw (obtained by the first approximation algorithm) linear discriminant
预测signature(object = "LdaPP")：计算预测的结果object。一个可选的数据框或矩阵中寻找变量，用以预测。如果省略，则使用训练数据集。 ，如果原始适合用一个公式或数据框或矩阵的列名，newdata必须包含列具有相同的名称。否则，它必须包含相同的列的数目，可以使用以相同的顺序。如果参数raw=TRUE设置的原料（通过以下方式获得的第一个近似算法）的线性判别
（作者）----------Author(s)----------
Valentin Todorov <a href="mailto:valentin.todorov@chello.at">valentin.todorov@chello.at</a> and
Ana Pires <a href="mailto:apires@math.ist.utl.pt">apires@math.ist.utl.pt</a>
参考文献----------References----------
Projection-pursuit approach to robust linear discriminant analysis Journal Multivariate Analysis, Academic Press, Inc., 101, 2464–2485.
An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. URL http://www.jstatsoft.org/v32/i03/.
参见----------See Also----------
LdaRobust-class, Lda-class, LdaClassic, LdaClassic-class, Linda, Linda-class
LdaRobust-class，Lda-class，LdaClassic，LdaClassic-class，Linda，Linda-class
实例----------Examples----------
showClass("LdaPP")
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 2012-9-28 20:46:53
