wave.multiple.correlation(wavemulcor)
wave.multiple.correlation()所属R语言包：wavemulcor
Wavelet routine for multiple correlation
小波常规多个相关
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Produces an estimate of the multiscale multiple correlation (as defined below) along with approximate confidence intervals.
产生一个近似置信区间估计的多尺度多的相关性（定义见下文）。
用法----------Usage----------
wave.multiple.correlation(xx, N, p = 0.975, ymaxr=NULL)
参数----------Arguments----------
参数：xx
A list of n (multiscaled) time series, usually the outcomes of dwt or modwt, i.e. xx <- list(v1.modwt.bw, v2.modwt.bw, v3.modwt.bw)
n（multiscaled）的时间序列列表，通常的结果的载重吨或modwt的，即XX < - 列表（v1.modwt.bw，v2.modwt.bw，v3.modwt.bw）
参数：N
length of the time series
时间序列的长度
参数：p
one minus the two-sided p-value for the confidence interval, i.e. the cdf value.
减去双侧P值的置信区间，即累积分布函数值之一。
参数：ymaxr
index number of the variable whose correlation is calculated against a linear combination of the rest, otherwise at each wavelet level wmc chooses the one maximizing the multiple correlation.
索引号的变量的相关计算针对其余的线性组合，否则在每个小波一级WMC选择一个最大化的多个相关。
Details
详细信息----------Details----------
The routine calculates one single set of wavelet multiple correlations out of n variables that can be plotted in a single graph, as an alternative to trying to make sense out of n(n-1)/2 sets of wavelet correlations. The code is based on the calculation, at each wavelet scale, of the square root of the coefficient of determination in the linear combination of variables for which such coefficient of determination is a maximum. The code provided here is based on the wave.correlation routine in Brandon Whitcher's waveslim R package Version: 1.6.4, which in turn is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001) and others.
值----------Value----------
List of two elements:<br> xy.mulcor: matrix with as many rows as levels in the wavelet transform object. The first column provides the point estimate for the wavelet multiple correlation, followed by the lower and upper bounds from the confidence interval.<br> YmaxR: numeric vector giving, at each wavelet level, the index number of the variable whose correlation is calculated against a linear combination of the rest. By default, wmc chooses at each wavelet level the variable maximizing the multiple correlation.
两个元素的列表的参考xy.mulcor：矩阵尽可能多的行水平的小波变换对象。的第一列提供的点估计的小波多重相关，随后从置信区间的下限和上限。参考YmaxR：数值向量在每个小波一级，发出，其相关性来计算对变量的索引号其余的一个线性组合。默认情况下，WMC选择在每个小波多个相关变量的最大化。
注意----------Note----------
Needs waveslim package to calculate dwt or modwt coefficients as inputs to the routine (also for data in the example).
需要waveslim包计算输入例程（在本例中的数据）的的载重吨，modwt系数为。
（作者）----------Author(s)----------
Javier Fern谩ndez-Macho,
Dpt. of Econometrics and Statistics,
& Instituto de Econom铆a P煤blica,
University of the Basque Country, Agirre Lehendakari etorb. 83, E48015 BILBAO, Spain.
(email: javier.fernandezmacho@ehu.es).
参考文献----------References----------
Fern谩ndez-Macho, Javier (2011) The wavelet multiple correlation, (mimeo).
实例----------Examples----------
## Based on data from Figure 7.8 in Gencay, Selcuk and Whitcher (2001)[]
## plus one random series.[＃加上一个随机序列。]
library(wavemulcor)
data(exchange)
returns <- diff(log(as.matrix(exchange)))
returns <- ts(returns, start=1970, freq=12)
wf <- "d4"
J <- 6
demusd.modwt <- modwt(returns[,"DEM.USD"], wf, J)
demusd.modwt.bw <- brick.wall(demusd.modwt, wf)
jpyusd.modwt <- modwt(returns[,"JPY.USD"], wf, J)
jpyusd.modwt.bw <- brick.wall(jpyusd.modwt, wf)
rand.modwt <- modwt(rnorm(length(returns[,"DEM.USD"])), wf, J)
rand.modwt.bw <- brick.wall(rand.modwt, wf)
xx <- list(demusd.modwt.bw, jpyusd.modwt.bw, rand.modwt.bw)
Lst <- wave.multiple.correlation(xx, N = length(xx[[1]][[1]]))
returns.modwt.cor <- Lst$xy.mulcor[1:J,]
YmaxR <- Lst$YmaxR
exchange.names <- c("DEM.USD", "JPY.USD", "RAND")
##Producing plot[＃生产图]
par(mfrow=c(1,1), las=0, mar=c(5,4,4,2)+.1)
matplot(2^(0 J-1)), returns.modwt.cor[-(J+1),], type="b",
log="x", pch="*LU", xaxt="n", lty=1, col=c(1,4,4),
xlab="Wavelet Scale", ylab="Wavelet Multiple Correlation")
axis(side=1, at=2^(0:7))
abline(h=0)
text(2^(0:7), min(returns.modwt.cor[-(J+1),])-0.03,
labels=exchange.names[YmaxR], adj=0.5, cex=.5)
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 2012-10-1 17:00:09
