AICc(sme)
AICc()所属R语言包:sme
The corrected AIC
校正的AIC
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Calculates the corrected AIC (AICc) of Hurvich and Tsai (1989). The AICc
计算的修正AIC(国际会议中心)的Hurvich和蔡(1989)。国际会议中心
用法----------Usage----------
AICc(object)
参数----------Arguments----------
参数:object
a fitted model object for which there exists a logLik method to extract the corresponding log-likelihood or an object inheriting from class logLik
一个合适的模型对象存在一个logLik的方法来提取相应的对数似然或对象继承自类logLik
Details
详细信息----------Details----------
AIC is an asymptotic result and may be inappropriate when the sample size is small, the number of estimated model parameters is large, or both. For the specific case of a linear model with homogeneous errors then Hurvich and Tsai (1989) derived a corrected AIC (AICc) which includes a correction for small sample sizes as AICc = AIC + (2*k*(k+1))/(n-k-1) where AIC is the standard AIC, k is the number of parameters in the model and n is the number of observations.
(AIC)因而是一个渐近的结果可能是不合适的,当样本大小是小的,估计的模型参数的数目是大的,或两者兼而有之。 Hurvich和蔡(1989)的特定情况下的线性模型均匀的错误,然后得出校正的AIC(国际会议中心),其中包括一个校正作为国际会议中心的小样本量= AIC +(2 * K *(k +1))/ (NK-1)其中,是标准AIC AIC,k是在模型中的参数的数量,n是观测值的数量。
While this is an exact result, it only applies in the very specific circumstances in which it was derived. However, as Burnham and Anderson (2002) point out, whenever the sample size is small some form of correction to the standard AIC is necessary, to the extent that they argue the AICc of Hurvich and Tsai (1989) should be used regardless of context unless a specific correction can be derived. In fact Burnham and Anderson (2004) go so far as to argue that it should be used irrespective of sample size as it tends to the standard AIC when n is large.
虽然这是一个确切的结果,它仅适用于在非常特殊的情况中,它派生。然而,伯纳姆和安德森(2002)指出,当样本规模小的标准AIC某种形式的修正是必要的,他们认为国际会议中心的Hurvich和蔡(1989)的范围内的情况下,应使用除非可以推导出一个特定的校正。事实上伯纳姆和安德森(2004)走那么远,认为它应适用的标准AIC当n足够大的样本量,因为它往往。
值----------Value----------
A numeric value with the AICc of the model
国际会议中心的模型的数值与
(作者)----------Author(s)----------
Maurice Berk <a href="mailto:maurice.berk01@imperial.ac.uk">maurice.berk01@imperial.ac.uk</a>
参考文献----------References----------
实例----------Examples----------
data(MTB)
fit <- sme(MTB[MTB$variable==6031,c("y","tme","ind")])
AICc(fit)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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