skewnormal1(VGAM)
skewnormal1()所属R语言包：VGAM
Univariate Skew-Normal Distribution Family Function
单变量斜正态分布家庭功能
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Maximum likelihood estimation of the shape parameter of a univariate skew-normal distribution.
一个单变量的偏移正常分布的形状参数的极大似然估计。
用法----------Usage----------
skewnormal1(lshape = "identity", earg = list(), ishape = NULL,
nsimEIM = NULL)
参数----------Arguments----------
参数：lshape, earg, ishape, nsimEIM
See Links and CommonVGAMffArguments.
见Links和CommonVGAMffArguments。
Details
详细信息----------Details----------
The univariate skew-normal distribution has a density function that can be written
单因素歪斜正态分布的密度函数，可以写入
where alpha is the shape parameter. Here, phi is the standard normal density and Phi its cumulative distribution function. When alpha=0 the result is a standard normal distribution. When alpha=1 it models the distribution of the maximum of two independent standard normal variates. When the absolute value of the shape parameter increases the skewness of the distribution increases. The limit as the shape parameter tends to positive infinity results in the folded normal distribution or half-normal distribution. When the shape parameter changes its sign, the density is reflected about y=0.
alpha的形状参数。在这里，phi是标准正态分布密度和Phi其累积分布函数。当alpha=0的结果是一个标准的正态分布。当alpha=1它的最大的两个独立标准正态分布随机分布模型。当的形状参数的绝对值增加的分布增加的偏度。为形状参数的极限的倾向正无穷大的查询结果，在倍数的正态分布或半正态分布。当形状参数改变符号，密度反映有关y=0。
The mean of the distribution is mu=alpha*sqrt(2/(pi*(1+alpha^2))) and these are returned as the fitted values. The variance of the distribution is 1-mu^2. The Newton-Raphson algorithm is used unless the nsimEIM argument is used.
平均的分布是mu=alpha*sqrt(2/(pi*(1+alpha^2)))和这些传回的拟合值。方差的分布是1-mu^2。牛顿 - 拉夫逊算法，除非使用nsimEIM参数用于使用。
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 ----------
It is well known that the EIM of Azzalini's skew-normal distribution is singular for skewness parameter tending to zero, and thus produces influential problems.
这是众所周知的，EIM Azzalini歪斜正态分布是奇异的偏度参数趋于零，从而产生影响力的问题。
注意----------Note----------
It is a good idea to use several different initial values to ensure that the global solution is obtained.
这是一个好主意，使用几个不同的初始值，以确保获得全球性的解决方案。
This family function will be modified (hopefully soon) to handle a location and scale parameter too.
这间家庭功能将被修改（希望很快）来处理的位置和尺度参数。
（作者）----------Author(s)----------
Thomas W. Yee
参考文献----------References----------
A class of distributions which include the normal. Scandinavian Journal of Statistics, 12, 171–178.
Statistical applications of the multivariate skew-normal distribution. Journal of the Royal Statistical Society, Series B, Methodological, 61, 579–602.
参见----------See Also----------
snorm, normal1, fnormal1.
snorm，normal1，fnormal1。
实例----------Examples----------
sdata <- data.frame(y = rsnorm(nn <- 1000, shape = 5))
fit <- vglm(y ~ 1, skewnormal1, sdata, trace = TRUE)
coef(fit, matrix = TRUE)
head(fitted(fit), 1)
with(sdata, mean(y))
## Not run: with(sdata, hist(y, prob = TRUE))[＃不运行：（SDATA，历史（Y，概率= TRUE））]
x <- with(sdata, seq(min(y), max(y), len = 200))
with(sdata, lines(x, dsnorm(x, shape = Coef(fit)), col = "blue"))
## End(Not run)[＃（不执行）]
sdata <- data.frame(x = runif(nn))
sdata <- transform(sdata, y = rsnorm(nn, shape = 1 + 2*x))
fit <- vglm(y ~ x, skewnormal1, sdata, trace = TRUE, crit = "coef")
summary(fit)
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。
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发表于 2012-10-1 15:53:34
