stslshac(sphet)
stslshac()所属R语言包：sphet
Spatial two stages least square with HAC standard errors
空间分为两个阶段最小二乘HAC标准误差
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Non-parametric heteroskedasticity and autocorrelation consistent (HAC) estimator of the variance-covariance (VC) for a vector of sample moments within a spatial context. The disturbance vector is generated as follows:
在一个空间范围内的样本矩的矢量非参数的异方差和自相关一致（HAC）估算的方差 - 协方差（VC）。上述干扰向量生成如下：
where R is a non-stochastic matrix.
R是一个非随机矩阵。
用法----------Usage----------
stslshac(formula, data=list(),listw,na.action=na.fail,zero.policy=NULL,
HAC=TRUE, distance=NULL,type=c("Epanechnikov","Triangular","Bisquare","Parzen", "QS","TH"),
bandwidth="variable",W2X=TRUE)
参数----------Arguments----------
参数：formula
a description of the model to be fit
描述的模型来适应
参数：data
an object of class data.frame. An optional data frame containing the variables in the model.
对象类数据框。一个可选的数据框包含在模型中的变量。
参数：listw
an object of class listw created for example by nb2listw
类的一个对象listw的nb2listw例如创建
参数：distance
an object of class distance created for example by read.gwt2dist The object contains the specification of the distance measure to be employed in the estimation of the VC matrix. See Details.
类的一个对象distance例如通过创建read.gwt2dist该对象包含在估计的VC矩阵可以采用规范的距离度量。查看详细信息。
参数：type
One of c("Epanechnikov","Triangular","Bisquare","Parzen", "QS","TH"). The type of Kernel to be used. See Details.
一个c("Epanechnikov","Triangular","Bisquare","Parzen", "QS","TH")。使用的类型的内核。查看详细信息。
参数：na.action
a function which indicates what should happen when the data contains missing values. See lm for details.
一个函数，它表示数据中包含缺失值的时会发生什么。请参阅流明的详细信息。
参数：zero.policy
See lagsarlm for details
lagsarlm的详细信息，
参数：bandwidth
"variable" (default) - or numeric when a fixed bandwidth is specified by the user.
“可变的”（缺省） - 或数字时，一个固定的带宽是由用户指定的。
参数：HAC
if FALSE traditional standard errors are provided.
如果的FALSE传统的标准误差。
参数：W2X
default TRUE. if FALSE only WX are used as instruments in the spatial two stage least squares.
默认为true。如果为FALSE只有WX在空间两阶段最小二乘法的工具。
Details
详细信息----------Details----------
The default sets the bandwith for each observation to the maximum distance for that observation (i.e. the max of each element of the list of distances).
默认设置对于每个观测到该观察（即最大的距离的列表的每个元素）的最大距离的带宽。
Six different kernel functions are implemented:
6个不同的内核功能的实现：
'Epanechnikov': K(z) = 1-z^2
'Epanechnikov'：K(z) = 1-z^2
'Triangular': K(z) = 1-z
'Triangular'：K(z) = 1-z
'Bisquare': K(z) = (1-z^2)^2
'Bisquare'：K(z) = (1-z^2)^2
'Parzen': K(z) = 1-6z^2+6 |z|^3 if z ≤q 0.5 and K(z) = 2(1-|z|)^3 if 0.5 < z ≤q 1
'Parzen'：K(z) = 1-6z^2+6 |z|^3如果z ≤q 0.5和 K(z) = 2(1-|z|)^3如果0.5 < z ≤q 1
'TH' (Tukey - Hanning): K(z) = \frac{1+ \cos(π z)}{2}
'TH'（杜克 - 汉宁）： K(z) = \frac{1+ \cos(π z)}{2}
'QS' (Quadratic Spectral): K(z) = \frac{25}{12π^2z^2} (\frac{\sin(6π z)/5)}{6π z/5} - \cos(6π z)/5)).
'QS'（二次谱）：K(z) = \frac{25}{12π^2z^2} (\frac{\sin(6π z)/5)}{6π z/5} - \cos(6π z)/5)）。
If the kernel type is not one of the six implemented, the function will terminate with an error message. The spatial two stage least square estimator is based on the matrix of instruments H=[X,WX,W^2X^2].
如果内核类型是不是一个的实现，该函数将终止并显示错误消息。的空间的两阶段最小二乘估计是根据文书H=[X,WX,W^2X^2]上的矩阵。
值----------Value----------
A list object of class sphet
一个List对象的类sphet
参数：coefficients
Spatial two stage least squares coefficient estimates
空间两阶段最小二乘估计系数
参数：vcmat
variance-covariance matrix of the estimated coefficients
方差 - 协方差矩阵的估计系数
参数：s2
S2sls residulas variance
S2sls residulas方差
参数：residuals
S2sls residuals
S2sls残差
参数：yhat
difference between residuals and response variable
残差和响应变量之间的差异
参数：call
the call used to create this object
用于创建此对象的调用
参数：model
the model matrix of data
的数据的模型矩阵
参数：type
the kernel employed in the estimation
内核采用的估计
参数：bandwidth
the type of bandwidth
的带宽类型
参数：method
's2slshac'
's2slshac'
（作者）----------Author(s)----------
Gianfranco Piras <a href="mailto:gpiras@mac.com">gpiras@mac.com</a>
参考文献----------References----------
HAC estimation in a spatial framework, Journal of Econometrics, 140, pages 131–154.
A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model, International Economic Review, 40, pages 509–533.
A Generalized Spatial Two Stage Least Square Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances, Journal of Real Estate Finance and Economics, 17, pages 99–121.
参见----------See Also----------
gstslshet, distance, distance
gstslshet，distance，distance
实例----------Examples----------
library(spdep)
data(columbus)
listw<-nb2listw(col.gal.nb)
data(coldis)
res<-stslshac(CRIME~HOVAL + INC, data=columbus,listw=listw, distance=coldis, type='Triangular')
summary(res)
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 2012-9-30 15:15:45
