summary.nls(stats)
summary.nls()所属R语言包：stats
Summarizing Non-Linear Least-Squares Model Fits
总结非线性最小二乘模型适合
译者：生物统计家园网 机器人LoveR
描述----------Description----------
summary method for class "nls".
summary类"nls"方法。
用法----------Usage----------
## S3 method for class 'nls'
summary(object, correlation = FALSE, symbolic.cor = FALSE, ...)
## S3 method for class 'summary.nls'
print(x, digits = max(3, getOption("digits") - 3),
symbolic.cor = x$symbolic.cor,
signif.stars = getOption("show.signif.stars"), ...)
参数----------Arguments----------
参数：object
an object of class "nls".
对象类"nls"。
参数：x
an object of class "summary.nls", usually the result of a call to summary.nls.
类对象"summary.nls"，通常是调用summary.nls的结果。
参数：correlation
logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.
逻辑; TRUE如果，估计参数的相关矩阵，则返回并打印。
参数：digits
the number of significant digits to use when printing.
打印时使用的有效位数的号码。
参数：symbolic.cor
logical. If TRUE, print the correlations in a symbolic form (see symnum) rather than as numbers.
逻辑。如果TRUE，在一个象征性的形式打印的相关性（见symnum），而不是数字。
参数：signif.stars
logical. If TRUE, "significance stars" are printed for each coefficient.
逻辑。如果TRUE，意义恒星的印有每个系数。
参数：...
further arguments passed to or from other methods.
通过进一步的论据或其他方法。
Details
详情----------Details----------
The distribution theory used to find the distribution of the standard errors and of the residual standard error (for t ratios) is based on linearization and is approximate, maybe very approximate.
基于线性分布理论中找到的标准误差和残留标准错误（T比值）的分布是近似的，也许非常近似。
print.summary.nls tries to be smart about formatting the coefficients, standard errors, etc. and additionally gives "significance stars" if signif.stars is TRUE.
print.summary.nls尝试聪明格式化的系数，标准误差等，另外给“意义星”signif.stars如果是TRUE的。
Correlations are printed to two decimal places (or symbolically): to see the actual correlations print summary(object)$correlation directly.
相关印两个小数（或符号）：看实际相关打印summary(object)$correlation直接。
值----------Value----------
The function summary.nls computes and returns a list of summary statistics of the fitted model given in object, using the component "formula" from its argument, plus
功能summary.nls计算并返回在object拟合模型的汇总统计列表，使用组件"formula"从它的参数，加上
参数：residuals
the weighted residuals, the usual residuals rescaled by the square root of the weights specified in the call to nls.
加权残值法，通常残差平方根的调用nls在指定的权重重新调整。
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矩阵的估计系数，标准误差，t-统计量和相应的（双面）p值的列。
参数：sigma
the square root of the estimated variance of the random error <p align="center">σ^2 = 1/(n-p) Sum(R[i]^2), where R[i] is the i-th weighted residual.
随机误差的估计方差的平方根<p ALIGN="CENTER">σ^2 = 1/(n-p) Sum(R[i]^2),其中R[i]是i次加权残值。
参数：df
degrees of freedom, a 2-vector (p, n-p). (Here and elsewhere n omits observations with zero weights.)
自由度，2向量(p, n-p)。 （在这里和其他地方n忽略具有零权的意见。）
参数：cov.unscaled
a p x p matrix of (unscaled) covariances of the parameter estimates.
p x p（未缩放）参数估计的协方差矩阵。
参数：correlation
the correlation matrix corresponding to the above cov.unscaled, if correlation = TRUE is specified and there are a non-zero number of residual degrees of freedom.
对应上面的相关矩阵cov.unscaled如果correlation = TRUE指定有非零数的残差自由度。
参数：symbolic.cor
(only if correlation is true.) The value of the argument symbolic.cor.
（只有correlation是真实的。）值参数symbolic.cor。
参见----------See Also----------
The model fitting function nls, summary.
该模型的拟合函数nls，summary。
Function coef will extract the matrix of coefficients with standard errors, t-statistics and p-values.
功能coef将提取的标准误，t-统计量和p值的系数矩阵。
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 2012-2-17 10:17:20
