threshold.wst(wavethresh)
threshold.wst()所属R语言包：wavethresh
Threshold (NDWT) packet-ordered non-decimated wavelet decomposition object
阈值（NDWT）数据包的排序的非抽取小波分解对象
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function provides various ways to threshold a wst class object
此功能提供了多种阈值一个wst类对象
用法----------Usage----------
## S3 method for class 'wst':
threshold(wst, levels = 3 nlevels(wst) - 1), dev = madmad, policy =
"universal", value = 0, by.level = FALSE, type = "soft", verbose
= FALSE, return.threshold = FALSE, cvtol = 0.01, cvnorm = l2norm,
add.history = TRUE, ...)
参数----------Arguments----------
参数：wst
The packet ordered non-decimated wavelet decomposition object that you wish to threshold.
包订购，非抽取小波分解的对象，你想阈值。
参数：levels
a vector of integers which determines which scale levels are thresholded in the decomposition. Each integer in the vector must refer to a valid level in the wst object supplied. This is usually any integer from 0 to nlevels(wst)-1 inclusive. Only the levels in this vector contribute to the computation of the threshold and its application.
决定哪些规模水平的阈值分解的向量整数。向量中的每个整数必须在wst对象提供一个有效的水平。这通常是从0到nlevels（WST）-1包容性的任一整数。只有在此向量的水平作出贡献的阈值的计算及其应用。
参数：dev
this argument supplies the function to be used to compute the spread of the absolute values coefficients. The function supplied must return a value of spread on the variance scale (i.e. not standard deviation) such as the var() function. A popular, useful and robust alternative is the madmad function
此参数提供的功能被用于计算的绝对值的系数的传播。提供的函数必须返回一个值传播的方差比例（即不标准差），如var()功能。一个流行的，有用的和强大的另一种方法是madmad功能
参数：policy
selects the technique by which the threshold value is selected. Each policy corresponds to a method in the literature. At present the different policies are: "universal", "LSuniversal", "sure", "cv", "manual", The policies are described in detail below.
选择被选择的阈值的技术，通过该技术。每个策略对应的方法在文献中。目前，不同的政策是：“universal”，“LSuniversal”，“sure”，“cv”，“manual”的政策中描述的详细below。
参数：value
This argument conveys the user supplied threshold. If the policy="manual" then value is the actual threshold value.
这个参数传递的用户提供的阈值。如果policy="manual"那么该值是实际的阈值。
参数：by.level
If FALSE then a global threshold is computed on and applied to all scale levels defined in levels. If TRUE a threshold is computed and applied separately to each scale level.
如果为FALSE，那么一个全球性的阈值计算，并适用于所有等级的定义在levels。如果真正的阈值计算，并分别应用到每一个规模水平。
参数：type
determines the type of thresholding this can be "hard" or "soft".
确定阈值的类型，这可能是“hard”或“soft”。
参数：verbose
if TRUE then the function prints out informative messages as it progresses.
如果真，那么该函数打印出的信息性消息，因为它的进展。
参数：return.threshold
If this option is TRUE then the actual value of the threshold is returned. If this option is FALSE then a thresholded version of the input is returned.
如果该选项是TRUE，则该阈值的实际值被返回。如果此选项为FALSE，则返回一个版本的输入阈值。
参数：cvtol
Parameter for the cross-validation "cv" policy.
参数的交叉验证“cv”政策。
参数：cvnorm
A function to compute the distance between two vectors. Two useful possibilities are l2norm and linfnorm. Selection of different metrics causes the cross-validation denoising method to optimize for different criteria.
一个函数来计算两个向量之间的距离。两个有用的功能是l2norm和linfnorm。选择不同的指标会导致交叉验证的去噪方法，以不同的标准进行优化。
参数：add.history
If TRUE then the thresholding operation details are add to the returned wst object. This can be useful when later tracing how an object has been treated.
如果TRUE阈值操作的详细信息添加到返回的wst对象。这可能是有用的，当后已被视为一个对象如何跟踪。
参数：...
any other arguments
任何其他参数
Details
详细信息----------Details----------
This function thresholds or shrinks wavelet coefficients stored in a wst object and returns the coefficients in a modified wst object. The thresholding step is an essential component of denoising using the packet-ordered non-decimated wavelet transform. If the denoising is carried out using the AvBasis basis averaging technique then this software is an implementation of the Coifman and Donoho translation-invariant (TI) denoising. (Although it is the denoising technique which is translation invariant, not the packet ordered non-decimated transform, which is translation equivariant). However, the threshold.wst algorithm can be used in other denoising techniques in conjunction with the basis selection and inversion functions MaNoVe and InvBasis.
此函数的阈值或缩小的小波系数存储在一个wst对象，并返回的改性wst对象中的系数。阈值的步骤是使用packet-ordered non-decimated wavelet transform去噪的一个重要组成部分。如果在去噪进行使用AvBasis基础上平均技术，那么这个软件的Coifman和Donoho平移不变性（TI）去噪的实现。 （虽然它是这是平移不变去噪技术，而不是数据包下令非抽取的变换，这是翻译等变）。然而，threshold.wst算法可以用于在其他的去噪技术结合的基础上选择和反转功能MaNoVe和InvBasis。
The basic idea of thresholding is very simple. In a signal plus noise model the wavelet transform of signal is very sparse, the wavelet transform of noise is not (in particular, if the noise is iid Gaussian then so if the noise contained in the wavelet coefficients). Thus since the signal gets concentrated in the wavelet coefficients and the noise remains "spread" out it is "easy" to separate the signal from noise by keeping large coefficients (which correspond to signal) and delete the small ones (which correspond to noise). However, one has to have some idea of the noise level (computed using the dev option in threshold functions). If the noise level is very large then it is possible, as usual, that no signal "sticks up" above the noise.
阈值的基本思想是非常简单的。在小波变换的信号的信号加噪声模型是很稀疏，小波变换等的噪声是不（特别是，如果噪声是独立同分布的高斯那么，如果包含的噪声在小波系数）。因此，由于得到的信号中的子波系数和浓缩噪声仍然“蔓延”出来，它是“容易”的分离信号从噪声中的保持大系数（对应的信号），和删除的小的（这对应于噪声） 。然而，有一些想法的噪声电平（使用dev选项的阈值函数计算）。如果噪声电平是非常大的，那么它是可能的，像往常一样，没有信号“，坚持”以上的噪音。
Many of the pragmatic comments for successful thresholding given in the help for threshold.wd hold true here: after all non-decimated wavelet transforms are merely organized collections of standard (decimated) discrete wavelet transforms. We reproduce some of the issues relevant to thresholding wst objects.
许多务实的帮助threshold.wd成功的阈值的意见成立后，所有非抽取小波变换的只是组织的标准离散小波变换（毁灭）的集合。我们复制一些阈值wst对象有关的问题。
Some issues to watch for:
注意的一些问题：
levels The default of levels = 3nlevels(wd) - 1) for the levels option most certainly does not work globally for all data problems and situations. The level at which thresholding begins (i.e. the given threshold and finer scale wavelets) is called the primary resolution and is unique to a particular problem. In some ways choice of the primary resolution is very similar to choosing the bandwidth in kernel regression albeit on a logarithmic scale. See Hall and Patil, (1995) and Hall and Nason (1997) for more information. For each data problem you need to work out which is the best primary resolution. This can be done by gaining experience at what works best, or using prior knowledge. It is possible to "automatically" choose a "best" primary resolution using cross-validation (but not yet in WaveThresh).
水平默认的levels = 3nlevels(wd) - 1)levels选项当然没有在全球范围的所有数据的问题和情况。在哪一级的阈值开始（即在给定的阈值和更细的刻度小波）被称为primary resolution和是唯一的一个特别的问题。在某些方面，主决议选择是非常类似的选择的带宽在内核回归尽管在对数刻度。见厅和Patil（1995）和霍尔和利晨（1997）更多信息。对于每一个数据的问题，你需要的工作，这是最好的小学分辨率。这是可以做到什么效果最好，获得经验或使用先验知识。这是可能的“自动”选择“最佳”的主要决议，采用交叉验证（但尚未WaveThresh）。
Secondly the levels argument computes and applies the threshold at the levels specified in the levels argument. It does this for all the levels specified. Sometimes, in wavelet shrinkage, the threshold is computed using only the finest scale coefficients (or more precisely the estimate of the overall noise level). If you want your threshold variance estimate only to use the finest scale coefficients (e.g. with universal thresholding) then you will have to apply the threshold.wd function twice. Once (with levels set equal to nlevels(wd)-1 and with return.threshold=TRUE to return the threshold computed on the finest scale and then apply the threshold function with the manual option supplying the value of the previously computed threshold as the value options.
其次，各级参数的阈值水平levels参数中指定的计算和应用。为此，它规定的水平。有时，在小波阈值，该阈值计算只用最好的比例系数（或更精确的估计的整体噪声水平）。如果您希望您的阈值的方差估计只有使用最好的规模系数（即通用阈值），那么你将不得不申请threshold.wd函数两次。一旦（级别设置等于nlevels（WD）-1return.threshold=TRUE返回上最优秀的规模计算的阈值，然后应用阈值函数的manual选项提供的价值先前计算的阈值value选项。
by.levelfor a wd object which has come from data with noise that is correlated then you should have a threshold computed for each resolution level. See the paper by Johnstone and Silverman, 1997.
by.levelfor一个wd对象来自相关的噪音，那么你应该有一个阈值，计算出每个分辨率级别的数据。约翰斯通和Silverman，1997年的文件。
值----------Value----------
An object of class wst. This object contains the thresholded wavelet coefficients. Note that if the return.threshold option is set to TRUE then the threshold values will be returned rather than the thresholded object.
对象的类wst。该对象包含阈值的小波系数。请注意，如果return.threshold选项被设置为TRUE，则阈值将被返回，而比阈值对象。
RELEASE----------RELEASE----------
Version 3.6 Copyright Guy Nason 1997
版本3.6版权所有1997年盖利晨
注意----------Note----------
This section gives a brief description of the different thresholding policies available. For further details see the associated papers. If there is no paper available then a small description is provided here. More than one policy may be good for problem, so experiment! Some of the policies here were specifically adapted to the This section gives a brief description of the different thresholding policies available. For further details see the associated papers. If there is no paper available then a small description is provided here. More than one policy may be good for problem, so experiment! Some of the policies here were specifically adapted to the wst.object but some weren't so beware. They are arranged here in alphabetical order:
本节给出了不同的阈值策略的简要说明。有关进一步详情，请参阅相关的文件。如果没有纸张可用，则一个小的描述在此提供。超过一个策略可能是很好的问题，所以实验！这里的一些政策，特别适合在本节给出了不同的阈值策略的简要说明。有关进一步详情，请参阅相关的文件。如果没有纸张可用，则一个小的描述在此提供。超过一个策略可能是很好的问题，所以实验！这里的一些政策，特别适合wst.object，“可是有些人不小心了。他们被安排在这里按字母顺序排列：
cvSee Nason, 1996.
利晨cvSee。
LSuniversalSee Nason, von Sachs and Kroisandt, 1998. This is used for smoothing of a wavelet periodogram and shouldn't be used generally.
LSuniversalSee利晨，冯高盛和Kroisandt，1998年。这是用于平滑化的小波周期图，一般不应使用。
manualspecify a user supplied threshold using value to pass the value of the threshold. The value argument should be a vector. If it is of length 1 then it is replicated to be the same length as the levels vector, otherwise it is repeated as many times as is necessary to be the levels vector's length. In this way, different thresholds can be supplied for different levels. Note that the by.level option has no effect with this policy.
manualspecify用户提供的阈值，使用value通过的阈值。 value参数应该是一个向量。如果它的长度为1，则它被复制到作为levels矢量是相同的长度，否则它被重复多次，水平向量的长度是必要的。以这种方式，可以提供不同的阈值的不同级别。需要注意的是by.level选项没有这个政策的影响。
sureSee Donoho and Johnstone, 1994 and Johnstone and Silverman, 1997.
sureSee Donoho和约翰斯通，1994年和Johnstone和Silverman，1997年。
universalSee Donoho and Johnstone, 1995.
universalSee Donoho和Johnstone，1995年。
（作者）----------Author(s)----------
G P Nason
参见----------See Also----------
AvBasis, AvBasis.wst, InvBasis, InvBasis.wst, MaNoVe,MaNoVe.wst, wst, wst.object, threshold.
AvBasis，AvBasis.wst，InvBasis，InvBasis.wst，MaNoVe，MaNoVe.wst，wst，wst.object，threshold。
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 2012-10-1 20:14:29
