locpoly(KernSmooth)
locpoly()所属R语言包：KernSmooth
Estimate Functions Using Local Polynomials
使用局部多项式估计函数
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Estimates a probability density function, regression function or their derivatives using local polynomials. A fast binned implementation over an equally-spaced grid is used.
估计概率密度函数，回归函数或其衍生物使用局部多项式。以上间距相等的网格分级实施快速使用。
用法----------Usage----------
locpoly(x, y, drv = 0L, degree, kernel = "normal",
bandwidth, gridsize = 401L, bwdisc = 25,
range.x, binned = FALSE, truncate = TRUE)
参数----------Arguments----------
参数：x
vector of x data. Missing values are not accepted.
X数据的向量。遗漏值是不能接受的。
参数：bandwidth
the kernel bandwidth smoothing parameter. It may be a single number or an array having length gridsize, representing a bandwidth that varies according to the location of estimation.
内核带宽平滑参数。它可能是一个单数或数组长度gridsize，占带宽，根据不同的估计位置。
参数：y
vector of y data. This must be same length as x, and missing values are not accepted.
Y数据的向量。这必须是相同的长度为x，遗漏值不被接受。
参数：drv
order of derivative to be estimated.
衍生金融工具，以估计。
参数：degree
degree of local polynomial used. Its value must be greater than or equal to the value of drv. The default value is of degree is drv + 1.
使用局部多项式程度。其值必须大于或等于的drv值。默认值是degree是drv+ 1。
参数：kernel
"normal" - the Gaussian density function. Currently ignored.
"normal" - 高斯密度函数。目前被忽略。
参数：gridsize
number of equally-spaced grid points over which the function is to be estimated.
间距相等的网格点的功能是将估计的数目。
参数：bwdisc
number of logarithmically-equally-spaced bandwidths on which bandwidth is discretised, to speed up computation.
bandwidth是离散化，以加快计算对数等间距的带宽数量。
参数：range.x
vector containing the minimum and maximum values of x at which to compute the estimate.
向量x在计算估计的最小值和最大值。
参数：binned
logical flag: if TRUE, then x and y are taken to be grid counts rather than raw data.
标志的逻辑：如果TRUE，则x和y格计数，而不是原始数据。
参数：truncate
logical flag: if TRUE, data with x values outside the range specified by range.x are ignored. </table>
逻辑标志：如果TRUE，x值range.x指定的范围之外的数据将被忽略。 </ TABLE>
值----------Value----------
if y is specified, a local polynomial regression estimate of E[Y|X] (or its derivative) is computed. If y is missing, a local polynomial estimate of the density of x (or its derivative) is computed.
如果y指定，局部多项式回归估计的E [Y | X]（或其衍生物）计算。 y如果缺少的x（或其衍生）密度局部多项式估计的计算。
a list containing the following components:
一个列表，包含以下组件：
参数：x
vector of sorted x values at which the estimate was computed.
向量排序x在计算估计值。
参数：y
vector of smoothed estimates for either the density or the regression at the corresponding x. </table>
密度或在相应的x回归平滑估计向量。 </ TABLE>
Details
详情----------Details----------
Local polynomial fitting with a kernel weight is used to estimate either a density, regression function or their derivatives. In the case of density estimation, the data are binned and the local fitting procedure is applied to the bin counts. In either case, binned approximations over an equally-spaced grid is used for fast computation. The bandwidth may be either scalar or a vector of length gridsize.
与粒重的局部多项式拟合是用来估计密度，回归函数或其衍生物。在密度估计的情况下，数据分级和当地装修过程中应用的bin计数。在这两种情况下，间距相等的网格分级近似的用于快速计算。带宽可以是标量或矢量长度gridsize。
参考文献----------References----------
Kernel Smoothing. Chapman and Hall, London.
参见----------See Also----------
bkde, density, dpill, ksmooth, loess, smooth, supsmu.
bkde，density，dpill，ksmooth，loess，smooth，supsmu。
举例----------Examples----------
data(geyser, package = "MASS")
# local linear density estimate[局部线性密度估计]
x <- geyser$duration
est <- locpoly(x, bandwidth = 0.25)
plot(est, type = "l")
# local linear regression estimate[局部线性回归估计]
y <- geyser$waiting
plot(x, y)
fit <- locpoly(x, y, bandwidth = 0.25)
lines(fit)
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 2012-2-16 18:06:29
