lqnorm(VGAM)
lqnorm()所属R语言包：VGAM
Minimizing the L-q norm Family Function
最小的L-Q规范家庭功能
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Minimizes the L-q norm of residuals in a linear model.
线性模型中的残差最小化的LQ规范。
用法----------Usage----------
lqnorm(qpower=2, link="identity", earg=list(),
imethod=1, imu=NULL, shrinkage.init=0.95)
参数----------Arguments----------
参数：qpower
A single numeric, must be greater than one, called q below. The absolute value of residuals are raised to the power of this argument, and then summed. This quantity is minimized with respect to the regression coefficients.
一个单一的数字，必须是大于1的，被称为q下面。残差的绝对值提出这种说法的力量，然后总结。相对于此的数量被最小化的回归系数。
参数：link, earg
Link function applied to the "mean" mu, and extra argument optionally used by the link function. See Links for more details.
Link功能应用到“的意思是”mu，和额外的参数可以使用链接功能。见Links更多详情。
参数：imethod
Must be 1, 2 or 3. See CommonVGAMffArguments for more information. Ignored if imu is specified.
必须是1，2或3。见CommonVGAMffArguments更多信息。如果忽略imu指定。
参数：imu
Numeric, optional initial values used for the fitted values. The default is to use imethod=1.
数字，可选的初始值，用于拟合值。的默认使用imethod=1。
参数：shrinkage.init
How much shrinkage is used when initializing the fitted values. The value must be between 0 and 1 inclusive, and a value of 0 means the individual response values are used, and a value of 1 means the median or mean is used. This argument is used in conjunction with imethod=3.
多少收缩时所使用的拟合值初始化。值必须介于0和1之间，0值是指个人的响应值，和值1中位数或平均数的。该参数用于结合与imethod=3。
Details
详细信息----------Details----------
This function minimizes the objective function
此函数的目标函数最小化
where q is the argument qpower, eta_i = g(mu_i) where g is the link function, and eta_i is the vector of linear/additive predictors. The prior weights w_i can be inputted using the weights argument of vlm/vglm/vgam etc.; it should be just a vector here since this function handles only a single vector or one-column response.
其中q的说法qpower，eta_i = g(mu_i)其中g的链接功能，和eta_i是向量的线性/添加剂的预测。前的权重w_i可以使用weights参数的输入vlm/vglm/vgam等;它应该只是一个向量，因为该功能只处理一个单一的矢量或一列反应。
Numerical problem will occur when q is too close to one. Probably reasonable values range from 1.5 and up, say. The value q=2 corresponds to ordinary least squares while q=1 corresponds to the MLE of a double exponential (Laplace) distibution. The procedure becomes more sensitive to outliers the larger the value of q.
时q实在是太近了一个数值的问题会发生。可能是合理的取值范围从1.5及更高说。值q=2对应于普通最小二乘法，而q=1对应的极大似然估计的双指数（拉普拉斯）发行套装。该过程变得更加敏感，异常值的值越大q。
值----------Value----------
An object of class "vglmff" (see vglmff-class). The object is used by modelling functions such as vglm, and vgam.
类的一个对象"vglmff"（见vglmff-class）。该对象被用于建模功能，如vglm，vgam。
警告----------Warning ----------
Convergence failure is common, therefore the user is advised to be cautious and monitor convergence!
收敛失败是很常见的，因此建议用户谨慎和显示器融合！
注意----------Note----------
This VGAM family function is an initial attempt to provide a more robust alternative for regression and/or offer a little more flexibility than least squares. The @misc slot of the fitted object contains a list component called objectiveFunction which is the value of the objective function at the final iteration.
这VGAM家庭功能是首次尝试的回归和/或提供更强大的替代品，比最小二乘提供多一点的灵活性。 @misc插槽的合身的对象包含一个列表组件objectiveFunction这是最后一次迭代的目标函数值。
（作者）----------Author(s)----------
Thomas W. Yee
参考文献----------References----------
Vector generalized additive models. Journal of the Royal Statistical Society, Series B, Methodological, 58, 481–493.
参见----------See Also----------
gaussianff.
gaussianff。
实例----------Examples----------
set.seed(123)
ldat = data.frame(x = sort(runif(nn <- 10 )))
realfun = function(x) 4 + 5*x
ldat = transform(ldat, y = realfun(x) + rnorm(nn, sd=exp(1)))
# Make the first observation an outlier[先观察一个局外人]
ldat = transform(ldat, y = c(4*y[1], y[-1]), x=c(-1, x[-1]))
fit = vglm(y ~ x, fam = lqnorm(qpower=1.2), data=ldat)
coef(fit, matrix=TRUE)
head(fitted(fit))
fit@misc$qpower
fit@misc$objectiveFunction
## Not run: [＃不运行：]
# Graphical check[图形检查]
with(ldat, plot(x, y, main=paste("LS=red, lqnorm=blue (qpower = ",
fit@misc$qpower, "), truth=black", sep=""), col="blue"))
lmfit = lm(y ~ x, data=ldat)
with(ldat, lines(x, fitted(fit), col="blue"))
with(ldat, lines(x, lmfit$fitted, col="red"))
with(ldat, lines(x, realfun(x), col="black"))
## End(Not run)[＃（不执行）]
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。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 15:43:05
