bw.smoothppp(spatstat)
bw.smoothppp()所属R语言包:spatstat
Cross Validated Bandwidth Selection for Spatial Smoothing
交叉验证的带宽选择的空间平滑
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Uses least-squares cross-validation to select a smoothing bandwidth for spatial smoothing of marks.
采用最小二乘法交叉验证,选择一个平滑的带宽空间平滑的标记。
用法----------Usage----------
bw.smoothppp(X, nh = spatstat.options("n.bandwidth"),
hmin=NULL, hmax=NULL, warn=TRUE)
参数----------Arguments----------
参数:X
A marked point pattern with numeric marks.
一个显着的数字标记点模式。
参数:nh
Number of trial values of smoothing bandwith sigma to consider. The default is 32.
试验的值平滑的带宽sigma的数考虑的问题。默认值是32。
参数:hmin, hmax
Optional. Numeric values. Range of trial values of smoothing bandwith sigma to consider. There is a sensible default.
可选。数值。范围的试验值的平滑带宽sigma考虑。有一个合理的默认。
参数:warn
Logical. If TRUE, issue a warning if the minimum of the cross-validation criterion occurs at one of the ends of the search interval.
逻辑。如果TRUE,发出警告,如果最小的交叉验证标准发生在搜索区间的端部之一。
Details
详细信息----------Details----------
This function selects an appropriate bandwidth for the nonparametric smoothing of mark values using smooth.ppp.
此功能选择合适的带宽使用smooth.ppp的标记值的非参数平滑。
The argument X must be a marked point pattern with a vector or data frame of marks. All mark values must be numeric.
参数X必须是显着的点模式与向量或数据框的标记。所有的标记值必须是数字。
The bandwidth is selected by least-squares cross-validation. Let y[i] be the mark value at the ith data point. For a particular choice of smoothing bandwidth, let y*[i] be the smoothed value at the ith data point. Then the bandwidth is chosen to minimise the squared error of the smoothed values sum (y[i] - y*[i])^2.
的带宽被选择由最小二乘交叉验证。让我们y[i]是在i个数据点的标记值。对于一个特定的平滑带宽的选择,让我们y*[i]是在i个数据点的平滑值。然后,带宽被选择以最小化的平滑值sum (y[i] - y*[i])^2的平方误差。
The result of bw.smoothppp is a numerical value giving the selected bandwidth sigma. The result also belongs to the class "bw.optim" allowing it to be printed and plotted. The plot shows the cross-validation criterion as a function of bandwidth.
bw.smoothppp的结果是一个数字值,给予选定的带宽sigma。结果也属于类"bw.optim"使其可以打印和绘制。图中显示的交叉验证标准的函数的带宽。
The range of values for the smoothing bandwidth sigma is set by the arguments hmin, hmax. There is a sensible default, based on the nearest neighbour distances.
范围值的平滑带宽sigma设定的参数hmin, hmax。是一个明智的默认情况下,根据最近的邻居距离。
If the optimal bandwidth is achieved at an endpoint of the interval [hmin, hmax], the algorithm will issue a warning (unless warn=FALSE). If this occurs, then it is probably advisable to expand the interval by changing the arguments hmin, hmax.
如果实现最佳的带宽在一个端点的时间间隔[hmin, hmax],该算法将发出警告(除非warn=FALSE“)。如果发生这种情况,那么它可能是可取的扩大的时间间隔改变的参数hmin, hmax。
Computation time depends on the number nh of trial values considered, and also on the range [hmin, hmax] of values considered, because larger values of sigma require calculations involving more pairs of data points.
计算时间依赖于数nh考虑的试验值,也取值范围为[hmin, hmax]考虑的,因为较大的值sigma需要涉及更多的对数据点的计算的值。
值----------Value----------
A numerical value giving the selected bandwidth. The result also belongs to the class "bw.optim" which can be plotted.
一个数值给选定的带宽。结果也属于类"bw.optim"可以绘制。
(作者)----------Author(s)----------
Adrian Baddeley
<a href="mailto:Adrian.Baddeley@csiro.au">Adrian.Baddeley@csiro.au</a>
<a href="http://www.maths.uwa.edu.au/~adrian/">http://www.maths.uwa.edu.au/~adrian/</a>
and Rolf Turner
<a href="mailto:r.turner@auckland.ac.nz">r.turner@auckland.ac.nz</a>
参见----------See Also----------
smooth.ppp
smooth.ppp
实例----------Examples----------
data(longleaf)
b <- bw.smoothppp(longleaf)
b
plot(b)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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