hoods2dsmooth(SpatialVx)
hoods2dsmooth()所属R语言包：SpatialVx
Wrapper functions for kernel2dsmooth
包装功能kernel2dsmooth
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Wrapper functions for kernel2dsmooth to perform specific convolution smooths of 2-d fields.
包装功能kernel2dsmooth执行特定的卷积平滑的2-D领域。
用法----------Usage----------
hoods2dsmooth(x, lambda, W = NULL, setup = FALSE, ...)
gauss2dsmooth(x, lambda, W = NULL, setup = FALSE, ...)
disk2dsmooth(x, lambda, W = NULL, setup = FALSE, ...)
identity2dsmooth(x, lambda = 0, W = NULL, setup = FALSE, ...)
参数----------Arguments----------
参数：x
numeric matrix giving the field to be smoothed.
数字矩阵的领域进行平滑。
参数：lambda
single numeric giving the smoothing parameter. In the case of hoods2dsmooth, this is the neighborhood length so that the result is that each point is an average over the nearest lambda^2 neighbors. For gauss2dsmooth, this is the sigma parameter, and for disk2dsmooth, this is the radius of the disk. Not used by identity2dsmooth.
单数字的平滑参数。在的情况下，hoods2dsmooth，这是周边的长度，这样的结果是，每个点是一个平均比最接近的lambda ^ 2的邻居。对于gauss2dsmooth，这是在sigma的参数，和disk2dsmooth，这是在磁盘的半径。不使用identity2dsmooth。
参数：W
(optional) if the FFT of the kernel weights have already been calculated for the smooth, they can be passed here. Not used by identity2dsmooth.
（可选），如果已计算出的内核权值的FFT的顺利，他们可以通过这里。不使用identity2dsmooth。
参数：setup
logical, should only the FFT of the kernel weights be returned (i.e., instead of the smoothed x field)? Should not be used if W is supplied, or you may not get what you want (i.e., precedence is given to W's being supplied). Not used by identity2dsmooth.
逻辑，只应的FFT的内核权值返回（即，上，而不是平滑的x域）？不应该使用W提供，或者你可能不会得到你想要的（即优先级W的供应）。不使用identity2dsmooth。
参数：...
optional arguments to the specific kernel type in the call to kernel2dsmooth, or really, to kernel2dmeitsjer. Not used by identity2dsmooth.
特定的内核类型的可选参数在调用kernel2dsmooth，还是真的，kernel2dmeitsjer。不使用identity2dsmooth。
Details
详细信息----------Details----------
This is a wrapper function to kernel2dsmooth. See its help file for more details. These functions were set up to make the hoods2d function more flexible (i.e., to allow other types of smoothing besides the default nearest neighbors smoothing). Makes use of the convolution theorem with the fast Fourier transform for computational efficiency (Ritter and Wilson, 2001; Barrett and Myers, 2004). Missing values are set to zero, and borders are zero-padded to an optimal amount. See Hastie and Tibshirani (1990) for smoothing functions in teh context fo statistical analysis.
这一个包装功能，kernel2dsmooth。有关详细信息，请参阅其帮助文件。这些功能使hoods2d功能更灵活的（即允许其他类型除了默认的近邻平滑平滑）。利用卷积定理与快速傅里叶变换的计算效率（Ritter和威尔逊，2001年，巴雷特和Myers，2004）。缺少的值被设置为零，和边框是用零填充，最佳量。 Hastie和Tibshirani（1990）平滑功能，在格兰上下文的FO统计分析。
hoods2dsmooth is a wrapper to kernel2dsmooth that employs the boxcar kernel with neighborhood length n as the smoothing parameter. This is the type of kernel smoothing proposed by Roberts and Lean (2008) and used in Ebert (2008). The smoothing parameter lambda should be an odd positive integer (though it need not be an actual integer recognized by R). If it is not, then one of several things will happen depending on its value, and a warning is generated. If it is not an integer (i.e., if floor(lambda) != lambda), the floor of lambda is taken. If it is even (possibly after flooring), one is subtracted from it. If it is less than one (possibly after flooring and/or subtracting one), it is set to one (note that if lambda = 1, the field x is returned untouched).
hoods2dsmooth是一个的包装到kernel2dsmooth，采用棚车内核，与邻里长度为n的平滑参数。这是提出由罗伯茨和精益生产（2008年）和艾伯特（2008年）中使用的核平滑的类型。的平滑化参数的lambda应为奇数的正整数（虽然它需要不是一个实际的确认由R的整数）。如果不是，那么几件事情之一会发生什么取决于它的价值，并产生一个警告。如果它不是一个整数（即，如果地板（λ）=拉姆达），地板的lambda采取。如果结果为偶数（可能后地板），一个是从中减去。如果它是小于1（可能在地板和/或减去1），它被设置为1（注意，如果λ= 1，则该字段返回x不变）。
gauss2dsmooth is a wrapper to kernel2dsmooth that employs the Gaussian kernel with smoothing parameter sigma. This is the type of smoothing applied originally for the practically perfect hindcast method (see Ebert, 2008).
gauss2dsmooth是一个包装到kernel2dsmooth中，采用高斯核平滑参数标准差。这是类型的平滑最初的几乎完美的事后评估方法（见艾伯特，2008年）。
disk2dsmooth is a wrapper to kernel2dsmooth that calls the disk kernel with smoothing parameter r (the radius of the disk). This is the type of smoothing applied in Davis et al. (2006a, 2006b).
disk2dsmooth是一个包装到kernel2dsmooth中调用磁盘的内核平滑参数r（半径的磁盘）。这是平滑施加在Davis等人的类型。 （2006年a，2006年b）。
identity2dsmooth simply returns the field without smoothing it. Provided for convenience.
identity2dsmooth简单地返回字段不平滑。提供了方便。
值----------Value----------
If W is not supplied and setup is TRUE, then a matrix is returned with dimensions chosen to optimize computational efficiency. Otherwise, a matrix of the same dimension as x is returned giving the smoothed version of the field.
如果W不提供和setup是TRUE，那么一个矩阵返回尺寸选择优化计算效率。否则，以矩阵的相同尺寸x返回给平滑的版本的字段。
（作者）----------Author(s)----------
Eric Gilleland
参考文献----------References----------
参见----------See Also----------
hoods2dPrep, hoods2d, kernel2dsmooth, kernel2dmeitsjer, fft
hoods2dPrep，hoods2d，kernel2dsmooth，kernel2dmeitsjer，fft
实例----------Examples----------
x <- y <- matrix( 0, 50, 50)
x[ sample(1:50,10), sample(1:50,10)] <- rexp( 100, 0.25)
y <- disk2dsmooth( x=x, lambda=6.5)
x <- gauss2dsmooth( x=x, lambda=3, nx=25, ny=25)
## Not run: [＃不运行：]
par( mfrow=c(1,2))
image.plot( x, col=tim.colors(256))
image.plot( y, col=tim.colors(256))
hold <- hoods2dPrep("y", "x", thresholds=c(0.1, 0.5), levels=c(1, 3, 20), smooth.fun="gauss2dsmooth", smooth.params=list(nx=601, ny=501))
look <- hoods2d( hold, which.methods=c("fss"))
plot( look)
data( pert000)
data(pert004)
# Do the neighborhood methods with averaging performed over a radius instead of the lambda^2 nearest neighbors.[做邻里的方法，取平均值进行，而不是在一个半径的lambda ^ 2个最近的邻居。]
# The smoothing parameters are determined by the levels argument, and the others are passed via smooth.params.[平滑参数是由参数水平，并传递通过smooth.params中。]
hold <- hoods2dPrep( "pert004", "pert000", thresholds=c(1,2,5,10,20,50), levels=c(1, 3, 9, 17, 33, 65, 129, 257),
smooth.fun="disk2dsmooth")
look <- hoods2d(hold, verbose=TRUE)
look
## End(Not run)[＃（不执行）]
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注：
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发表于 2012-9-30 12:56:39
