amlexponential(VGAM)
amlexponential()所属R语言包：VGAM
Exponential Regression by Asymmetric Maximum Likelihood Estimation
不对称的最大似然估计的指数回归
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Exponential expectile regression estimated by maximizing an asymmetric likelihood function.
最大化非对称似然函数，的指数expectile回归估计。
用法----------Usage----------
amlexponential(w.aml = 1, parallel = FALSE, imethod = 1, digw = 4,
link = "loge", earg = list())
参数----------Arguments----------
参数：w.aml
Numeric, a vector of positive constants controlling the expectiles. The larger the value the larger the fitted expectile value (the proportion of points below the “w-regression plane”). The default value of unity results in the ordinary maximum likelihood (MLE) solution.
数字，一个矢量控制expectiles的正的常数。该值越大，较大的拟合expectile值（点以下的“w回归平面的比例”）。统一的默认值的查询结果在普通的最大似然（MLE）溶液。
参数：parallel
If w.aml has more than one value then this argument allows the quantile curves to differ by the same amount as a function of the covariates. Setting this to be TRUE should force the quantile curves to not cross (although they may not cross anyway). See CommonVGAMffArguments for more information.
如果w.aml有一个以上的值，则此参数允许不同的协变量的函数相同数额的位数曲线。设置TRUE应该迫使位数曲线不交叉（尽管他们可能不能跨越反正）。见CommonVGAMffArguments更多信息。
参数：imethod
Integer, either 1 or 2 or 3. Initialization method. Choose another value if convergence fails.
整数，1或2或3。初始化方法。选择另一个值，如果收敛失败。
参数：digw
Passed into Round as the digits argument for the w.aml values; used cosmetically for labelling.
传递到Rounddigits参数w.aml的值;用于美容标签。
参数：link, earg
See exponential and the warning below.
见exponential和下面的警告。
Details
详细信息----------Details----------
The general methodology behind this VGAM family function is given in Efron (1992) and full details can be obtained there. This model is essentially an exponential regression model (see exponential) but the usual deviance is replaced by an asymmetric squared error loss function; it is multiplied by w.aml for positive residuals. The solution is the set of regression coefficients that minimize the sum of these deviance-type values over the data set, weighted by the weights argument (so that it can contain frequencies). Newton-Raphson estimation is used here.
这背后VGAM家庭功能的一般方法给出了埃弗龙（1992），在那里可以得到的全部细节。这种模式本质上是一种指数回归模型（见exponential），但一般的越轨行为被替换为一个非对称的平方误差损失函数，它是乘以w.aml积极残差。该解决方案是一套，最大限度地减少这些偏差类型的值的总和以上的数据集，加权weights参数（以便它可以包含频率）的回归系数。这里使用Newton-Raphson法估计。
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和vgam。
警告----------Warning ----------
Note that the link argument of exponential and amlexponential are currently different: one is the rate parameter and the other is the mean (expectile) parameter.
请注意，link参数exponential，和amlexponential目前不同的：一个是速率参数，和另一种是的平均值（expectile）参数。
If w.aml has more than one value then the value returned by deviance is the sum of all the (weighted) deviances taken over all the w.aml values. See Equation (1.6) of Efron (1992).
如果w.aml有一个以上的值，然后返回的值deviance的所有（加权）deviances的接管所有w.aml值的总和。 ·埃夫隆（1992），见公式（1.6）。
注意----------Note----------
On fitting, the extra slot has list components "w.aml" and "percentile". The latter is the percent of observations below the “w-regression plane”, which is the fitted values. Also, the individual deviance values corresponding to each element of the argument w.aml is stored in the extra slot.
配件，extra插槽列表组件"w.aml"和"percentile"。后者是％以下的“w回归平面”，这是对于拟合值的观测。此外，个别越轨值对应于每个元素的参数w.aml被存储在extra插槽。
For amlexponential objects, methods functions for the generic functions qtplot and cdf have not been written yet.
对于amlexponential对象，方法，功能的通用功能qtplot和cdf还没有被写入尚未。
See amlpoisson about comments on the jargon, e.g., expectiles etc.
请参阅amlpoisson有关的术语的意见，例如，expectiles
In this documentation the word quantile can often be interchangeably replaced by expectile (things are informal here).
在本文档中字位数经常被交替更换expectile（这里的东西都是非正式的）。
（作者）----------Author(s)----------
Thomas W. Yee
参考文献----------References----------
Poisson overdispersion estimates based on the method of asymmetric maximum likelihood. Journal of the American Statistical Association, 87, 98–107.
参见----------See Also----------
exponential, amlbinomial, amlpoisson, amlnormal, alaplace1, lms.bcg, deexp.
exponential，amlbinomial，amlpoisson，amlnormal，alaplace1，lms.bcg，deexp。
实例----------Examples----------
nn = 2000
mydat = data.frame(x = seq(0, 1, length = nn))
mydat = transform(mydat, mu = loge(-0+1.5*x+0.2*x^2, inverse = TRUE))
mydat = transform(mydat, mu = loge(0-sin(8*x), inverse = TRUE))
mydat = transform(mydat, y = rexp(nn, rate = 1/mu))
(fit = vgam(y ~ s(x,df = 5), amlexponential(w = c(0.001,0.1,0.5,5,60)),
mydat, trace = TRUE))
fit@extra
## Not run: # These plots are against the sqrt scale (to increase clarity)[＃不运行：＃这些图的对开方规模的（增加清晰度）]
par(mfrow = c(1,2))
# Quantile plot[分量图]
with(mydat, plot(x, sqrt(y), col = "blue", las = 1, main =
paste(paste(round(fit@extra$percentile, dig = 1), collapse = ", "),
"percentile-expectile curves")))
with(mydat, matlines(x, sqrt(fitted(fit)), lwd = 2, col = "blue", lty = 1))
# Compare the fitted expectiles with the quantiles[与分位数，比较合身的expectiles，]
with(mydat, plot(x, sqrt(y), col = "blue", las = 1, main =
paste(paste(round(fit@extra$percentile, dig = 1), collapse = ", "),
"percentile curves are orange")))
with(mydat, matlines(x, sqrt(fitted(fit)), lwd = 2, col = "blue", lty = 1))
for(ii in fit@extra$percentile)
with(mydat, matlines(x, sqrt(qexp(p = ii/100, rate = 1/mu)), col = "orange"))
## 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。
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发表于 2012-10-1 15:24:53
