rho2hat(spatstat)
rho2hat()所属R语言包：spatstat
Smoothed Relative Density of Pairs of Covariate Values
平滑相对密度对协变量值
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Given a point pattern and two spatial covariates Z1 and Z2, construct a smooth estimate of the relative risk of the pair (Z1, Z2).
由于一个点图案和两个空间的协变量Z1和Z2，建立一个流畅的估计的相对危险性对(Z1, Z2)。
用法----------Usage----------
rho2hat(object, cov1, cov2, ..., method=c("ratio", "reweight"))
参数----------Arguments----------
参数：object
A point pattern (object of class "ppp"), a quadrature scheme (object of class "quad") or a fitted point process model (object of class "ppm").
点模式（类的对象"ppp"），一个正交计划（类的对象"quad"）或拟合点过程模型（类的对象"ppm"）。
参数：cov1,cov2
The two covariates. Each argument is either a function(x,y) or a pixel image (object of class "im") providing the values of the covariate at any location, or one of the strings "x" or "y" signifying the Cartesian coordinates.
这两个协变量。每个参数可以是一个function(x,y)或像素图像（对象类"im"）提供的协变量的值，在任何地点，或之一的字符串"x"或"y"标志着在直角坐标系。
参数：...
Additional arguments passed to density.ppp to smooth the scatterplots.
额外的参数传递给density.ppp顺利的散点图。
参数：method
Character string determining the smoothing method. See Details.
字符串确定平滑方法。查看详细信息。
Details
详细信息----------Details----------
This is a bivariate version of rhohat.
这是一个二元版本的rhohat。
If object is a point pattern, this command produces a smoothed version of the scatterplot of the values of the covariates cov1 and cov2 observed at the points of the point pattern.
如果object是一个点模式，这个命令会产生一个平滑的协变量的值的散点图cov1和cov2观察点的点模式。
The covariates cov1,cov2 must have continuous values.
协变量cov1,cov2必须具有连续值。
If object is a fitted point process model, suppose X is the original data point pattern to which the model was fitted. Then this command assumes X is a realisation of a Poisson point process with intensity function of the form
object如果是一个拟合点过程模型，假设X的原始数据点图案的模型拟合。然后，该命令将假定X是一个实现函数的形式与强度的泊松点过程
where kappa(u) is the intensity of the fitted model object, and rho(z1, z2) is a function to be estimated. The algorithm computes a smooth estimate of the function rho.
其中kappa(u)的强度的拟合模型object，rho(z1, z2)是一个函数进行估计。该算法计算出一个平滑估计的函数rho。
The method determines how the density estimates will be combined to obtain an estimate of rho(z1, z2):
决定如何密度估计将合并，以获得method估计rho(z1, z2)：
If method="ratio", then rho(z1,z2) is estimated by the ratio of two density estimates. The numerator is a (rescaled) density estimate obtained by smoothing the points (Z1(y[i]), Z2(y[i])) obtained by evaluating the two covariate Z1, Z2 at the data points y[i]. The denominator is a density estimate of the reference distribution of (Z1, Z2).
如果method="ratio"，那么rho(z1,z2)估计两个密度估计的比例。分子是通过以下方式获得平滑的点（重新缩放）密度估计(Z1(y[i]), Z2(y[i]))进行评价得到的两个协变量Z1, Z2在数据点y[i]。分母为密度估计的参考分布(Z1, Z2)。
If method="reweight", then rho(z1,z2) is estimated by applying density estimation to the points (Z1(y[i]), Z2(y[i])) obtained by evaluating the two covariate Z1, Z2 at the data points y[i], with weights inversely proportional to the reference density of (Z1, Z2).
如果method="reweight"，然后rho(z1,z2)通过施加密度估计的点估计(Z1(y[i]), Z2(y[i]))进行评价得到的两个协变量Z1, Z2在数据点y[i]，权重成反比的参考密度(Z1, Z2)。
值----------Value----------
A pixel image (object of class "im"). Also belongs to the special class "rho2hat" which has a plot method.
像素的图像（类的对象"im"“）。也属于类特殊"rho2hat"有一个图方法。
（作者）----------Author(s)----------
Adrian Baddeley
参考文献----------References----------
Nonparametric estimation of the dependence of a point process on spatial covariates. Statistics and Its Interface 5 (2), 221–236.
参见----------See Also----------
rhohat, methods.rho2hat
rhohat，methods.rho2hat
实例----------Examples----------
data(bei)
attach(bei.extra)
plot(rho2hat(bei, elev, grad))
fit <- ppm(bei, ~polynom(elev, 3), covariates=bei.extra)
plot(rho2hat(fit, elev, grad))
plot(rho2hat(fit, elev, grad, method="reweight"))
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。
|
发表于 2012-9-30 14:06:25
