scarm.filter(robfilter)
scarm.filter()所属R语言包：robfilter
SCARM (Slope Comparing Adaptive Repeated Median)
SCARM（斜坡比较自适应反复中位数）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
A procedure for robust online signal extraction from univariate time series by a moving window technique with adaptive window width selection based on the Repeated Median regression
从单变量时间序列的重复中位数回归的移动窗口技术与自适应窗口宽度选择的强大的网络信号提取的过程
用法----------Usage----------
scarm.filter(x, right.width=15, min.left.width=right.width, min.width=floor(right.width/3), max.width=200, sign.level=0.001, bound.slope.diff=0, bound.noise.sd=0, rtr=TRUE)
参数----------Arguments----------
参数：x
a numeric vector or (univariate) time series object.
一个数值向量或单变量时间序列对象。
参数：right.width
a positive integer >=5 defining the fixed width of the right-hand window used for testing; the choice of right.width is crucial to distinguish between a patch of outliers and a signal change.
一个正整数> = 5，确定用于测试的右侧窗口中选择固定宽度的right.width来区分补丁的异常和信号变化是至关重要的。
参数：min.left.width
a positive integer ≥ right.width defining the minimum width of the left-hand window used for testing.
一个正整数≥right.width的左手的用于测试的窗口定义的最小宽度。
参数：min.width
a positive integer ≥ 5 specifying the minimum window width.
一个正整数≥ 5指定的最小的窗口宽度。
参数：max.width
a positive integer ≥ min.width and ≥ right.width + min.left.width specifying the maximum window width.
一个正整数≥min.width和≥right.width+min.left.width指定窗口的最大宽度。
参数：sign.level
significance level of the test procedure; must be a value in (0,0.5).
显着性水平的测试程序，必须是一个值(0,0.5)。
参数：bound.slope.diff
a lower bound for the absolute difference of the Repeated Median slopes in the left-hand and right-hand window; if this absolute difference is smaller than 'bound.slope.diff', the window width is not decreased; must be a value > 0.
的下限差的绝对值的的重复中位数斜坡的左侧和右侧窗口中;如果这绝对差较小比“bound.slope.diff”，，窗口宽度不下降，必须是一个值> 0。
参数：bound.noise.sd
a lower bound for the estimation of the noise standard deviation; this bound ensures that the noise estimation is zero due to ties in the data; must be a value > 0.
一个下界估计的噪声标准差;，这个结合可确保噪音估计是零由于在数据的关系;必须有一个值> 0。
参数：rtr
if rtr=TRUE, the signal estimation is restricted to the range of the rightmost min.width observations.
如果rtr=TRUE，信号估计的被限制的范围内的最右边的min.width观测。
Details
详细信息----------Details----------
The scarm.filter works by applying Repeated Median (RM) regression (Siegel, 1982) to a moving time window with a length varying between min.width and max.width.
该scarm.filter的工作原理是将重复中位数（RM）的回归（西格尔，1982年）的移动时间窗口的长度变化之间min.width和最大宽度。
For each point in time, the window width is adapted to the current data situation by a test which is based on the comparison of two RM slopes estimated in separated sub-windows, a right-hand and a left-hand window.
对于每个时间点，将窗口宽度适于当前的数据的情况下，两个RM的斜坡中估计的比较，它是基于通过一个测试分离的子窗口，右手和左手的窗口。
A more detailed description of the filter can be found in Borowski and Fried (2012).
的过滤器的更详细的描述可以发现在博罗夫斯基和Fried（2012年）。
值----------Value----------
scarm.filter returns an object of class scarm.filter. An object of class scarm.filter is a list containing the following components:
scarm.filter返回一个对象类scarm.filter。一个对象的类scarm.filter的是一个列表，其中包含以下组件：
参数：signal.est
a vector containing the signal estimations
一个向量，包含信号估计
参数：slope.est
a vector containing the slope estimations
一个向量，包含的斜率估计
参数：adapted.width
a vector containing the adapted window widths
一个向量，包含适于窗口宽度
参数：test.statistic
a vector containing the SCARM test statistics
一个向量，包含SCARM测试统计
参数：critvals
a vector containing the critical values for test decision
一个向量，包含用于测试决定的临界值
参数：noise.sd
a vector containing the noise standard deviation estimated by a regression-free scale estimator (Gelper et al., 2009)
一个向量，包含噪声标准差估计的回归规模估计（Gelper等人，2009年）
参数：slope.diff
a vector containing the differences of the Repeated Median slopes estimated in the left-hand and right-hand window
一个向量，包含在左侧和右侧窗口中的重复中位数斜坡估计的差异
In addition, the original input data and the input arguments used for the analysis are returned as list members.
此外，用于分析的原始输入数据和输入参数返回作为列表成员。
Application of the function plot to an object of class scarm.filter returns a plot showing the original time series with the filtered output.
应用的功能plot对象的类scarm.filter返回一个图，显示的原始时间序列的过滤输出。
（作者）----------Author(s)----------
Matthias Borowski
参考文献----------References----------
Robust moving window regression for online signal extraction from non-stationary time series: online window width adaption by testing for signal changes, submitted.<br>
Robust online scale estimation in time series: A model-free approach, Journal of Statistical Planning and Inference, 139 (2), 335-349.<br>
Robust Regression Using Repeated Medians, Biometrika 69 (1), 242-244.<br>
参见----------See Also----------
robreg.filter, adore.filter, madore.filter.
robreg.filter，adore.filter，madore.filter。
实例----------Examples----------
# # # # # # # # # #[＃＃＃＃＃＃＃＃＃]
# Short and noisy time series[短期和嘈杂的时间序列]
data(multi.ts)
x <- multi.ts[,1]
# SCARM Filter [SCARM过滤器]
scarm.extr <- scarm.filter(x)
plot(scarm.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 21:04:40
