summary.manova(stats)
summary.manova()所属R语言包:stats
Summary Method for Multivariate Analysis of Variance
多元方差分析方法概要
译者:生物统计家园网 机器人LoveR
描述----------Description----------
A summary method for class "manova".
一个summary类"manova"方法。
用法----------Usage----------
## S3 method for class 'manova'
summary(object,
test = c("Pillai", "Wilks", "Hotelling-Lawley", "Roy"),
intercept = FALSE, tol = 1e-7, ...)
参数----------Arguments----------
参数:object
An object of class "manova" or an aov object with multiple responses.
一个类的对象"manova"或aov多个响应的对象。
参数:test
The name of the test statistic to be used. Partial matching is used so the name can be abbreviated.
要使用的检验统计量的名称。部分匹配使用这样的名字可以缩写。
参数:intercept
logical. If TRUE, the intercept term is included in the table.
逻辑。如果TRUE,截距项被列入表中。
参数:tol
tolerance to be used in deciding if the residuals are rank-deficient: see qr.
容忍在决定使用残差秩缺陷:qr。
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 summary.manova method uses a multivariate test statistic for the summary table. Wilks' statistic is most popular in the literature, but the default Pillai–Bartlett statistic is recommended by Hand and Taylor (1987).
summary.manova方法使用多元试验统计汇总表。威尔克斯的统计数据是最流行的文学,但手和泰勒(1987)建议的默认皮莱巴特利特统计。
The table gives a transformation of the test statistic which has approximately an F distribution. The approximations used follow S-PLUS and SAS (the latter apart from some cases of the Hotelling–Lawley statistic), but many other distributional approximations exist: see Anderson (1984) and Krzanowski and Marriott (1994) for further references. All four approximate F statistics are the same when the term being tested has one degree of freedom, but in other cases that for the Roy statistic is an upper bound.
下表给出了一个测试统计,大约有一个F分布的转变。近似使用,S-PLUS和SAS(后者除了霍特林罗礼统计某些情况下),但存在许多其他分布近似:看到安德森(1984)和Krzanowski和万豪酒店(1994年)作进一步参考。所有四个近似F统计量是相同的,当被测试的术语有一个自由度,但在其他情况下,罗伊统计是一个上限。
The tolerance tol is applied to the QR decomposition of the residual correlation matrix (unless some response has essentially zero residuals, when it is unscaled). Thus the default value guards against very highly correlated responses: it can be reduced but doing so will allow rather inaccurate results and it will normally be better to transform the responses to remove the high correlation.
宽容tol残余相关矩阵的QR分解(除非一些回应基本上是零的残差,当它被缩放的)。因此,对反应非常高度相关的默认值警卫:可以减少,但这样做将使相当准确的结果,通常会是更好的改造,以消除高相关。