ROWCov(RTAQ)
ROWCov()所属R语言包：RTAQ
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Function returns the Realized Outlyingness Weighted Covariance, defined in Boudt et al. (2008).
功能返回实现Outlyingness，加权协方差，定义在Boudt等。 （2008年）。
Let r_{t,i}, for i=1,...,M be a sample of M high-frequency (N x 1) return vectors and d_{t,i} their outlyingness given by the squared Mahalanobis distance between the return vector and zero in terms of the reweighted MCD covariance estimate based on these returns.
让我们r_{t,i}，i=1,...,M是一个样本M高频(N x 1)返回向量和d_{t,i}你自己的outlyingness，返回向量之间的马氏距离平方重加权MCD协方差为零，估计这些回报的基础上。
Then, the ROWCov is given by
然后，由下式给出的ROWCov
The weight w_{i,Δ} is one if the multivariate jump test statistic for r_{i,Δ} in Boudt et al. (2008) is less than the 99.9% percentile of the chi-square distribution with N degrees of freedom and zero otherwise. The scalar c_{w} is a correction factor ensuring consistency of the ROWCov for the Integrated Covariance, under the Brownian Semimartingale with Finite Activity Jumps model.
的重量w_{i,Δ}如果r_{i,Δ}在Boudt等多元跳检验统计量为1。 （2008）小于99.9％的百分位数的卡方分布N程度的自由，否则为零。标量c_{w}为修正系数确保一致性的ROWCov的综合协方差，有限的活动跳跃模型下的布朗半鞅。
用法----------Usage----------
ROWCov(rdata, cor = FALSE, makeReturns=FALSE, seasadjR = NULL,
wfunction = "HR" , alphaMCD = 0.75, alpha = 0.001,...)
参数----------Arguments----------
参数：rdata
a (M x N) matrix/zoo/xts object containing the N return series over period t, with M observations during t.
一个(M x N)矩阵/动物园/ XTS在过段N对象包含t收益率序列，M在t观察。
参数：cor
boolean, in case it is TRUE, the correlation is returned. FALSE by default.
布尔值，如果是TRUE，则返回相关。默认情况下，返回FALSE。
参数：makeReturns
boolean, should be TRUE when rdata contains prices instead of returns. FALSE by default.
布尔值，应该是TRUE时RDATA包含价格，而不是返回。默认情况下，返回FALSE。
参数：seasadjR
a (M x N) matrix/zoo/xts object containing the seasonaly adjusted returns. This is an optional argument.
(M x N)矩阵/动物园/ XTS物件，其中包含的seasonaly调整后的回报。这是一个可选的参数。
参数：wfunction
determines whether a zero-one weight function (one if no jump is detected based on d_{t,i} and 0 otherwise) or Soft Rejection ("SR") weight function is to be used. By default a zero-one weight function (wfunction = "HR") is used.
确定是否一个零1的权重函数（一个跳转时，如果没有检测到基于d_{t,i}，否则为0）或软抑制（“SR”）权函数为要使用。缺省情况下为零的一个权重函数（wfunction =“HR”）被使用。
参数：alphaMCD
a numeric parameter, controlling the size of the subsets over which the determinant is minimized. Allowed values are between 0.5 and 1 and the default is 0.75. See Boudt et al. (2008) or the covMcd function in the robustbase package.
一个数值参数，控制行列式最小的子集的大小。允许的值是0.5~1之间，默认值是0.75。见Boudt等。 （2008）或covMcd功能在robustbase包。
参数：alpha
is a parameter between 0 en 0.5, that determines the rejection threshold value (see Boudt et al. (2008) for details).
0 EN 0.5之间，是一个参数，决定拒绝阈值（见Boudt等人（2008）的详细信息）。
参数：...
additional arguments.
其他参数。
Details
详细信息----------Details----------
Advantages of the ROWCov compared to the RBPCov include a higher statistical efficiency, positive semidefiniteness and affine equivariance. However, the ROWCov suffers from a curse of dimensionality. Indeed, the ROWCov gives a zero weight to a return vector if at least one of the components is affected by a jump. In the case of independent jump occurrences, the average proportion of observations with at least one component being affected by jumps increases fast with the dimension of the series. This means that a potentially large proportion of the returns receives a zero weight, due to which the ROWCov can have a low finite sample efficiency in higher dimensions
的ROWCov的优点相比，RBPCov包括更高的统计效率，正半定和仿射equivariance的。然而，ROWCov遭受诅咒的维。事实上，ROWCov给出了一个回报矢量，如果权重为零的组件中的至少一个的是，受由跳转。在独立的跳跃出现的情况下，与观测的平均比例的至少一种成分的影响与该系列的尺寸快速增加的跳跃。这意味着，一个潜在的大比例的返回接收一个零的重量，由于其中的ROWCov可以具有低的在高维有限样本效率
值----------Value----------
an N x N matrix
N x N矩阵
（作者）----------Author(s)----------
Jonathan Cornelissen and Kris Boudt
参考文献----------References----------
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。
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发表于 2012-9-28 22:37:18
