madore.filter(robfilter)
madore.filter()所属R语言包：robfilter
A multivariate adaptive online repeated median filter
多变量自适应在线重复中值滤波
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Procedure for robust signal extraction from a multivariate time series by a moving window technique with adaptive window width selection (multivariate adaptive online repeated median filter). The window width adaption is based on the univariate adore.filter.
多变量时间序列的移动窗口技术与自适应窗口宽度选择可靠的信号提取的程序（多变量自适应在线重复中值滤波器）。的窗口宽度适应的基础上的单变量adore.filter。
用法----------Usage----------
madore.filter(Y, byrow=FALSE, min.width=10, max.width=200, test.sample.size=min.width/2, width.search="geometric", rtr.size=min.width, alpha=0.1, NA.sample.size=min.width, minNonNAs=min.width/2)
参数----------Arguments----------
参数：Y
a numeric matrix or (multivariate) time series object.
一个数字矩阵（多元）时间序列对象。
参数：byrow
logical. If FALSE (the default), the filtering is done by columns, otherwise the filtering is done by rows.
逻辑。如果FALSE（默认值），过滤是通过列，否则过滤是通过行。
参数：min.width
a positive integer ≥ 10 specifying the minimal width of the moving time window.
一个正整数≥ 10指定的移动的时间窗口中的最小宽度。
参数：max.width
a positive integer ≥ min.width specifying the maximal width of the moving time window. If min.width = max.width, the window width is fixed.
一个正整数≥min.width的移动时间窗口中指定的最大宽度。如果min.width=max.width，窗口的宽度是固定的。
参数：test.sample.size
a positive integer in [5, min.width] defining a test window of the rightmost test.sample.size time points within the current time window. The Repeated Median (RM) regression residuals within the test window are used for a goodness of fit test (see adore.filter) for finding an adequate window width. For more details about the test, see Schettlinger, Fried, Gather (2008).
[5中的正整数，min.width]定义一个测试窗口的最右边的test.sample.size时间点在当前时间窗口内。重复中位数（RM）在测试窗口的回归残差的拟合优度检验（见adore.filter）找到一个适当的窗口宽度。有关测试的更多详细信息，请参阅Schettlinger，油煎，收集（2008年）。
参数：width.search
a character string defining the search algorithm used for finding an adequate window width at each point in time.
限定的搜索算法的字符串，用于在每个时间点上找到一个足够的窗口宽度。
"linear"The linear search always results in the largest window width possible and hence yields the smoothest online signal. However, if sudden changes (like level shifts) appear in the signal it requires a lot of computation time and thus, an increased variability of the extracted signal may be observed.
"linear"的线性搜索都会导致在可能的最大窗口宽度，从而产生流畅的在线信号。然而，如果在该信号中出现的突然变化（如电平漂移），它需要大量的计算时间，从而可以观察到，所提取的信号的增加的变异。
"binary"The binary search is recommended if it can be expected that the window width needs to be reduced drastically from a large to a very small value at certain times (for example at level shifts or trend changes). However, it may not always result in the largest possible window width.
"binary"的二进制搜索建议，如果是可以预期，需要大幅减少到一个非常小的值，在特定的时间（例如，在电平漂移或趋势的变化）从一个大的窗口宽度。但是，它可能并不总是导致的最大可能的窗口宽度。
"geometric" (default)The geometric search is as fast as the binary search but it puts more weight on large window widths. It offers a good compromise between the linear and the binary search (computation time vs. smooth output signal).
"geometric"（默认）的几何搜索的二进制搜索一样快，但它把更多的重量，大窗口的宽度。它提供了一个很好的妥协之间的线性和二进制搜索（计算时间与平滑的输出信号）。
参数：rtr.size
a non-negative integer specifying the size of a subset of the most recent observations within each window. The signal estimation is restricted to the range of the observations within this subset.
一个非负的整数，用于指定在每个窗口内的最近的观测的一个子集的大小。这个子集内的信号估计的被限制的范围内的观察。
参数：alpha
the level of significance for the goodness of fit test (see adore.filter) for finding an adequate window width. For more details about the test, see Schettlinger, Fried, Gather (2008).
的拟合优度检验的显着水平（见adore.filter）找到一个适当的窗口宽度。有关测试的更多详细信息，请参阅Schettlinger，油煎，收集（2008年）。
参数：NA.sample.size
a positive integer in [10, min.width] specifying the size of a subset of the most recent observations within each window. See minNonNAs.
[10中的正整数，min.width]指定的大小的一个子集的每个窗口内的最近的观测。见minNonNAs。
参数：minNonNAs
a positive integer in [5, NA.sample.size]. If a variable does not offer at least minNonNAs non-missing observations within the subset specified by NA.sample.size, the signal is not estimated for this variable at this time point t.
一个正整数[5，NA.sample.size]。如果一个变量不提供至少minNonNAs非缺失观测的子集内指定的NA.sample.size，信号没有估计这个变量在这个时间点t。
Details
详细信息----------Details----------
The madore.filter is based on Repeated Median regression (Siegel, 1982) in moving time windows and serves for separating signals from noise and outliers in multivariate time series. At each time point t the test procedure of the adaptive online Repeated Median filter (Schettlinger, Fried, Gather, 2008) is used to determine an appropriate window width n(t) in [min.width, max.width]. Then the signal vector at time t is estimated within the time window (t-n(t)+1,…,t) by a slight modification of the multivariate Trimmed Repeated Median-Least Squares regression (Lanius, Gather, 2004). A more detailed description of the madore.filter can be found in Borowski, Schettlinger, Gather (2009).
madore.filter的基础上反复中位数回归（西格尔，1982），中移动的时间窗口，用于在多变量时间序列分离信号从噪声和异常点。在每个时间点t中值滤波（Schettlinger，炒，收集，2008年）是用来确定一个合适的窗口宽度的自适应在线重复的测试程序n(t)[min.width， max.width]。然后时间窗口内的信号矢量的时间t估计(t-n(t)+1,…,t)稍微修改的多元修剪过反复位数最小二乘回归（伯劳，收集，2004年）。 madore.filter更详细的说明可以发现博罗夫斯基Schettlinger，收集（2009年）。
值----------Value----------
madore.filter returns an object of class madore.filter. An object of class madore.filter is a list containing the following components:
madore.filter返回一个对象类madore.filter。一个对象的类madore.filter的是一个列表，其中包含以下组件：
参数：signals
a matrix containing the estimated signal vectors at each time point t.
一个矩阵包含在每个时间点t的估计的信号矢量。
参数：widths
a matrix containing the individual window widths of each variable at each time point t.
包含每个变量的各个窗口的宽度的矩阵，在每个时间点t。
参数：overall.width
a vector containing the overall window widths at each time point t.
一个向量，包含在每个时间点t的整体的窗口宽度。
In addition, the original input data is returned as list member Y, and the settings used for the analysis are returned as the list members byrow, min.width, max.width, start.width, test.sample.size, width.search, rtr.size, extr.delay, NA.sample.size, and minNonNAs. Application of the function plot to an object of class madore.filter returns a plot showing the original multivariate time series with the filtered output.
此外，原始输入数据的形式返回列表成员Y，用于分析和设置返回列表成员byrow，min.width，max.width， start.width，test.sample.size，width.search，rtr.size，extr.delay，NA.sample.size和minNonNAs。应用的功能plot对象的类madore.filter返回原来的多变量时间序列的过滤输出的图。
（作者）----------Author(s)----------
Matthias Borowski
参考文献----------References----------
Multivariate Real Time Signal Extraction by a Robust Adaptive Regression Filter, Communications in Statistics - Simulation and Computation 38, 426-440.<br>
Robust Online Signal Extraction from Multivariate Time Series, Technical Report 38/07, SFB 475, Universit盲t Dortmund, Germany.<br>
Real Time Signal Processing by Adaptive Repeated Median Filters, International Journal of Adaptive Control and Signal Processing, Special Issue on 'Signal Processing and Diagnosis: Biomedical Applications', to appear.<br>
Robust Regression Using Repeated Medians, Biometrika 69 (1), 242-244.<br>
参见----------See Also----------
robreg.filter, adore.filter.
robreg.filter，adore.filter。
实例----------Examples----------
data(multi.ts)
extr <- madore.filter(multi.ts)
plot(extr)
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 2012-9-27 21:03:28
