summary.lts(robustbase)
summary.lts()所属R语言包：robustbase
Summary Method for LTS objects
LTS对象的方法摘要
译者：生物统计家园网 机器人LoveR
描述----------Description----------
summary method for class "lts".
summary方法类"lts"。
用法----------Usage----------
## S3 method for class 'lts'
summary(object, correlation = FALSE, ...)
## S3 method for class 'summary.lts'
print(x, digits = max(3, getOption("digits") - 3),
signif.stars = getOption("show.signif.stars"), ...)
参数----------Arguments----------
参数：object
an object of class "lts", usually, a result of a call to ltsReg.
类的一个对象"lts"，通常，一个结果，调用ltsReg。
参数：correlation
logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.
逻辑，如果TRUE，相关矩阵的估计的参数返回和印刷。
参数：x
an object of class "summary.lts", usually, a result of a call to summary.lts.
类的一个对象"summary.lts"，通常，一个结果，调用summary.lts。
参数：digits
the number of significant digits to use when printing.
打印时所使用的数量显著数字。
参数：signif.stars
logical indicating if “significance stars” should be printer, see printCoefmat.
逻辑表示“的意义明星”应该是打印机，printCoefmat。
参数：...
further arguments passed to or from other methods.
进一步的参数传递给其他方法。
Details
详细信息----------Details----------
These functions compute and print summary statistics for weighted least square estimates with weights based on LTS estimates. Therefore the statistics are similar to those for LS but all terms are multiplied by the corresponding weight.
Correlations are printed to two decimal places: to see the actual correlations print summary(object)$correlation directly.
打印到小数点后两位的相关性：看实际的相关打印summary(object)$correlation直接。
值----------Value----------
The function summary.lts computes and returns a list of summary statistics of the fitted linear model given in object, using the components of this object (list elements).
的功能summary.lts计算，并返回一个列表，在object拟合的线性模型的汇总统计，使用该对象的组件列表中的元素。
参数：residuals
the residuals - a vector like the response y containing the residuals from the weighted least squares regression.
残差 - 一个向量，如响应y加权最小二乘回归的残差。
参数：coefficients
a p x 4 matrix with columns for the estimated coefficient, its standard error, t-statistic and corresponding (two-sided) p-value.
p x 4矩阵列的估计系数及其标准误，t-统计量和相应的p值（双面）。
参数：sigma
the estimated scale of the reweighted residuals <p align="center"> sigma^2 = 1/(n-p) Sum(R[i]^2), where R[i] is the i-th residual, residuals[i].
重加权残差的估计规模<p ALIGN="CENTER"> sigma^2 = 1/(n-p) Sum(R[i]^2),其中R[i]是i个剩余，residuals[i]。
参数：df
degrees of freedom, a 3-vector (p, n-p, p*), the last being the number of non-aliased coefficients.
自由度，3矢量(p, n-p, p*)，最后即非失真系数的数目。
参数：fstatistic
(for models including non-intercept terms) a 3-vector with the value of the F-statistic with its numerator and denominator degrees of freedom.
（模型包括非-截距术语）的3矢量F统计量的值与它的分子和分母自由度。
参数：r.squared
R^2, the “fraction of variance explained by the model”, <p align="center"> R^2 = 1 - Sum(R[i]^2) / Sum((y[i]- y*)^2), where y* is the mean of y[i] if there is an intercept and zero otherwise.
R^2，“方差分数由模型解释”，<p /> R^2 = 1 - Sum(R[i]^2) / Sum((y[i]- y*)^2),其中y*是y[i]的平均值，如果有一个拦截，否则为零。
参数：adj.r.squared
the above R^2 statistic “adjusted”, penalizing for higher p.
上述R^2统计“调整”，处罚对高p。
参数：cov.unscaled
a p x p matrix of (unscaled) covariances of the coef[j], j=1, …, p.
p x p矩阵（无标度）的协方差coef[j]，j=1, …, p。
参数：correlation
the correlation matrix corresponding to the above cov.unscaled, if correlation = TRUE is specified.
对应于上述的相关矩阵cov.unscaled，如果correlation = TRUE被指定。
----------See Also----------
ltsReg; the generic summary.
ltsReg;通用summary。
实例----------Examples----------
data(Animals2)
ltsA <- ltsReg(log(brain) ~ log(body), data = Animals2)
(slts <- summary(ltsA))
## non-default options for printing the summary:[＃非默认的选项打印摘要：]
print(slts, digits = 5, signif.stars = FALSE)
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 2012-9-27 22:15:51
