wavFDPBand(wmtsa)
wavFDPBand()所属R语言包：wmtsa
Mid-octave spectral density function (SDF) estimation
中倍频程谱密度函数（SDF）估计
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The wavelet and scaling filters used for wavelet decompositions are nominally associated with approximate bandpass filters. Specifically, at decomposition level j, the wavelet transform coefficients correspond approximately to the normalized frequency range of [ 1/2^(j+1), 1 /2^j ]. The square of the wavelet coefficients are used to form the so-called wavelet variance (or wavelet spectrum) which is seen as a regularization of the SDF. Under an assumed FD process, this function estimates the mid-octave SDF values. The estimates are calculated assuming that the wavelet transform filters form perfect (rectangular) passbands. Decomposition levels 1 and 2 are calculated using a second order Taylor series expansion about the mid-octave frequencies while, for levels greater than 2, a small angle approximation (sin(pi * f) ~ pi * f) is used to develop a closed form solution which is a function of
名义上用于小波分解的小波和尺度滤波器与近似的带通滤波器。具体而言，在分解级j，小波变换系数对应约[ 1/2^(j+1), 1 /2^j ]的归一化频率范围。的小波系数的平方被用来形成所谓的小波方差（或小波频谱），这被看作是一个制式化自卫队。在一个假设的FD过程中，这个函数估计中八度的SDF值。估计的计算假设，小波变换过滤器形成完美的（矩形）通带。层层分解1和2的计算采用二阶泰勒级数展开的中八度的频率，同时，水平大于2，小角度近似（sin(pi * f) ~ pi * f ）是用来开发一个封闭的形式的解决方案，这是一个功能
用法----------Usage----------
参数----------Arguments----------
参数：delta
the fractional difference parameter. If the scaling band estimates are desired (prompted by setting n.sample > 0), then delta must be less than 0.5 since the formulae for calculating the scaling band estimates implicitly assume stationarity. Default: 0.4.
分数差参数。如果缩放频带估计所需的（提示通过设置n.sample > 0），然后delta必须小于0.5时间的公式用于计算缩放频带估计隐含地假定平稳。默认值：0.4。
参数：levels
a vector containing the decomposition levels. If n.sample <= 0, then the levels may be given in any order and levels may be skipped. If, however, n.sample > 0, then levels must contain the values 1, 2, 3, ..., J where J is the maximum wavelet transform decomposition level. Default: 1:5.
一个向量的分解水平。如果n.sample <= 0，然后水平可以以任何顺序和层次可以跳过。然而，如果n.sample>0，然后levels必须包含的值1, 2, 3, ..., J其中J是最大的小波变换的分解级别。默认值：1:5。
参数：method
a character string denoting the method to be used for estimating the average spectral density values at the center frequency (on a log scale) of each DWT octave. The choices are
一个字符的字符串表示的方法被用于估算的平均谱密度在中心频率处的值（对数标度）的每个DWT的倍频程。的选择
"integration"Numerical integration of the standard FDP spectral density function.
"integration"FDP的标准谱密度函数的数值积分。
"bandpass"A small angle approximation to the standard FDP spectral density functions for decomposition levels j >= 3 in combination with a Taylor series approximation for levels j=1,2.
"bandpass"的小角度近似的标准FDP层层分解谱密度函数为j >= 3结合泰勒级数近似的水平j=1,2。
Default: "bandpass".
默认值："bandpass"。
参数：n.sample
the number of samples in the time series. Although no time series is actually passed to the wavFDPBand function, the n.sample argument is used in estimating the mid-octave SDF value over the band of frequencies which are nominally associated with the scaling filter in a wavelet transform. If n.sample > 0, this function will append the estimate of the average SDF value over the scaling band to the wavelet octave estimates. If n.sample <= 0, only the wavelet octave estimates are returned. Default: 1024.
在时间序列中的采样数。虽然没有时间序列实际上是传递给wavFDPBand功能，n.sample参数是用来在名义上与尺度滤波器的小波变换在整个频段的频率估计中八度的SDF值。如果n.sample > 0，此功能将追加SDF的平均估计值在比例带的小波八度的估计。如果n.sample <= 0，只有小波倍频程估计将返回。默认值：1024。
参数：scaling
a logical flag. If TRUE, the mid-octave value of the FDP SDF octave corresponding to the scaling coefficients is also returned. Default: TRUE.
一个逻辑标志。如果TRUE，中期八度的FDP SDF倍频程，相应的比例系数也将返回值。默认值：TRUE。
Details
详细信息----------Details----------
Estimates are made for the scaling filter band based upon an implicit assumption that the FD process is stationary (delta < 0.5).
估计是一个隐含的假设，FD过程是平稳的（delta < 0.5）根据尺度滤波器带。
值----------Value----------
a vector containing the mid-octave SDF estimates for an FD process.
一个向量，包含FD过程中八度的SDF估计。
参考文献----------References----------
D. B. Percival and A. T. Walden, Wavelet Methods for Time Series Analysis, Cambridge University Press, 2000, 343–54.
参见----------See Also----------
实例----------Examples----------
## calculate the mid-octave SDF values for an FD [＃计算中八度的SDF值的FD]
## process over various wavelet bands [＃处理过各种小波带]
wavFDPBand(levels=c(1, 3, 5:7), delta=0.45, scaling=FALSE)
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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 22:54:19
