vcovHC(sandwich)
vcovHC()所属R语言包：sandwich
Heteroskedasticity-Consistent Covariance Matrix Estimation
异方差一致协方差矩阵的估计
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Heteroskedasticity-consistent estimation of the covariance matrix of the coefficient estimates in regression models.
在回归模型中异方差的一致估计系数的协方差矩阵的估计。
用法----------Usage----------
vcovHC(x, ...)
## Default S3 method:[默认方法]
vcovHC(x,
type = c("HC3", "const", "HC", "HC0", "HC1", "HC2", "HC4", "HC4m", "HC5"),
omega = NULL, sandwich = TRUE, ...)
meatHC(x, type = , omega = NULL)
参数----------Arguments----------
参数：x
a fitted model object.
拟合模型对象。
参数：type
a character string specifying the estimation type. For details see below.
一个字符串指定的估计类型。有关详细信息，请参阅下文。
参数：omega
a vector or a function depending on the arguments residuals (the working residuals of the model), diaghat (the diagonal of the corresponding hat matrix) and df (the residual degrees of freedom). For details see below.
根据参数的不同的向量或一个函数residuals（工作残差的模型），diaghat（对角线对应的帽子矩阵）和df（残差自由度） 。有关详细信息，请参阅下文。
参数：sandwich
logical. Should the sandwich estimator be computed? If set to FALSE only the meat matrix is returned.
逻辑。三明治估计计算？如果设置为FALSE只有肉类矩阵返回。
参数：...
arguments passed to sandwich.
参数传递到sandwich。
Details
详细信息----------Details----------
The function meatHC is the real work horse for estimating the meat of HC sandwich estimators – the default vcovHC method is a wrapper calling sandwich and bread. See Zeileis (2006) for more implementation details. The theoretical background, exemplified for the linear regression model, is described below and in Zeileis (2004).
函数meatHC是真正的工作的马为估计HC三明治估值的肉 - 默认vcovHC方法是一个包装调用sandwich和bread。具体的实现细节，请参阅Zeileis（2006）。的线性回归模型中，例举的理论背景，下面描述和在Zeileis（2004）。
When type = "const" constant variances are assumed and and vcovHC gives the usual estimate of the covariance matrix of the coefficient estimates:
当type = "const"恒定的差异被认为和vcovHC给出了通常的估计系数的协方差矩阵估计：
All other methods do not assume constant variances and are suitable in case of heteroskedasticity. "HC" (or equivalently "HC0") gives White's estimator, the other estimators are refinements of this. They are all of form
所有其他方法不承担恒定的差异和适合的情况下，异方差性。 "HC"（或等效"HC0"）为白色的估计，估计是完善了这一。他们都是形式
and differ in the choice of Omega. This is in all cases a diagonal matrix whose elements can be either supplied as a vector omega or as a a function omega of the residuals, the diagonal elements of the hat matrix and the residual degrees of freedom. For White's estimator
和不同的选择的Omega。这是在所有情况下的对角矩阵，其元素既可以供给的向量omega或氨基酸功能omega的残差，帽子矩阵的对角线元素和残差自由度。对于白色的估计
omega <- function(residuals, diaghat, df) residuals^2
omega <- function(residuals, diaghat, df) residuals^2
Instead of specifying the diagonal omega or a function for estimating it, the type argument can be used to specify the HC0 to HC5 estimators. If omega is used, type is ignored.
而不是指定用于估计它的对角线的omega或一个函数，type参数可以用于指定HC0 HC5估计。如果omega，type被忽略。
Long \& Ervin (2000) conduct a simulation study of HC estimators (HC0 to HC3) in the linear regression model, recommending to use HC3 which is thus the default in vcovHC. Cribari-Neto (2004), Cribari-Neto, Souza, \& Vasconcellos (2007), and Cribari-Neto \& Da Silva (2011), respectively, suggest the HC4, HC5, and modified HC4m type estimators. All of them are tailored to take into account the effect of leverage points in the design matrix. For more details see the references.
\和欧文（2000年）进行了仿真研究的HC估计（HC0以HC3）的线性回归模型，建议使用HC3，因此默认情况下，在vcovHC。克里巴里，内托（2004年），克里巴里，内托，索萨，\＆Vasconcellos（2007）的，和克里巴里托\＆达席尔瓦（2011），分别提示HC4，HC5，并修改HC4m型估计。针对所有这些都考虑到影响的平衡点在设计矩阵。有关详细信息，请参阅参考资料。
值----------Value----------
A matrix containing the covariance matrix estimate.
一个矩阵的协方差矩阵的估计。
参考文献----------References----------
of unknown form. Computational Statistics \& Data Analysis 45, 215–233.
covariance matrix estimator for the linear regression model. Advances in Statistical Analysis, 95(2), 129–146.
heteroskedasticity and leveraged data. Communications in Statistics – Theory and Methods, 36, 1877–1888. Errata: 37, 3329–3330, 2008.
Errors in the Linear Regression Model. The American Statistician, 54, 217–224.
covariance matrix estimators with improved finite sample properties. Journal of Econometrics 29, 305–325.
a direct test for heteroskedasticity. Econometrica 48, 817–838.
Estimators. Journal of Statistical Software, 11(10), 1–17. URL http://www.jstatsoft.org/v11/i10/.
Journal of Statistical Software, 16(9), 1–16. URL http://www.jstatsoft.org/v16/i09/.
参见----------See Also----------
lm, hccm,
lm，hccm，
实例----------Examples----------
## generate linear regression relationship[＃生成线性回归关系]
## with homoskedastic variances[，＃与homoskedastic差异]
x <- sin(1:100)
y <- 1 + x + rnorm(100)
## model fit and HC3 covariance[＃模型的拟合和HC3协方差]
fm <- lm(y ~ x)
vcovHC(fm)
## usual covariance matrix[＃通常的协方差矩阵]
vcovHC(fm, type = "const")
vcov(fm)
sigma2 <- sum(residuals(lm(y ~ x))^2)/98
sigma2 * solve(crossprod(cbind(1, x)))
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注：
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发表于 2012-9-29 22:14:12
