laplace(VGAM)
laplace()所属R语言包：VGAM
Laplace Distribution
拉普拉斯分布
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Maximum likelihood estimation of the 2-parameter classical Laplace distribution.
最大似然估计的2个参数的经典拉普拉斯分布。
用法----------Usage----------
laplace(llocation = "identity", lscale = "loge", elocation = list(),
escale = list(), ilocation = NULL, iscale = NULL,
imethod = 1, zero = 2)
参数----------Arguments----------
参数：llocation, lscale
Character. Parameter link functions for location parameter a and scale parameter b. See Links for more choices.
字符。参数的链接功能，位置参数a和尺度参数b。见Links更多的选择。
参数：elocation, escale
List. Extra argument for each of the links. See earg in Links for general information.
列表。每个环节的额外参数。见earg中Links的一般信息。
参数：ilocation, iscale
Optional initial values. If given, it must be numeric and values are recycled to the appropriate length. The default is to choose the value internally.
可选的初始值。如果给出，则它必须是数字和值被再循环到适当的长度。默认情况下是选择内部的价值。
参数：imethod
Initialization method. Either the value 1 or 2.
初始化方法。无论的值1或2。
参数：zero
See CommonVGAMffArguments for more information.
见CommonVGAMffArguments更多信息。
Details
详细信息----------Details----------
The Laplace distribution is often known as the double-exponential distribution and, for modelling, has heavier tail than the normal distribution. The Laplace density function is
拉普拉斯分布通常被称为双指数分布，建模，有较重的尾部比正态分布。拉普拉斯密度函数是
where -Inf<y<Inf, -Inf<a<Inf and b>0. Its mean is a and its variance is 2b^2. This parameterization is called the classical Laplace distribution by Kotz et al. (2001), and the density is symmetric about a.
-Inf<y<Inf，-Inf<a<Inf和b>0。均值为a和方差为2b^2。这种参数被称为经典的拉普拉斯分布科茨等。 （2001），和密度是对称a。
For y ~ 1 (where y is the response) the maximum likelihood estimate (MLE) for the location parameter is the sample median, and the MLE for b is mean(abs(y-location)) (replace location by its MLE if unknown).
对于y ~ 1（其中y是响应）的位置参数是最大似然估计（MLE）的样本中位数和最大似然估计b是mean(abs(y-location))（更换位置由其MLE如果不知道）。
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----------
This family function has not been fully tested. The MLE regularity conditions do not hold for this distribution, therefore misleading inferences may result, e.g., in the summary and vcov of the object.
这间家庭功能还没有得到充分的测试。的MLE的规律性条件并不持有这种分布，因此可能会导致误导性的推论，例如，在summary和vcov的对象。
注意----------Note----------
This family function uses Fisher scoring. Convergence may be slow for non-intercept-only models; half-stepping is frequently required.
此的家庭功能使用费舍尔得分。非仅截距模型的收敛速度可能很慢，经常需要半步。
（作者）----------Author(s)----------
T. W. Yee
参考文献----------References----------
The Laplace distribution and generalizations: a revisit with applications to communications, economics, engineering, and finance, Boston: Birkhauser.
参见----------See Also----------
rlaplace, alaplace2 (which differs slightly from this parameterization), exponential, median.
rlaplace，alaplace2（略有不同，从这个参数化），exponential，median。
实例----------Examples----------
lddat = data.frame(y = rlaplace(nn <- 100, loc = 2, scale = exp(1)))
fit = vglm(y ~ 1, laplace, lddat, trace = TRUE, crit = "l")
coef(fit, matrix = TRUE)
Coef(fit)
with(lddat, median(y))
lddat = data.frame(x = runif(nn <- 1001))
lddat = transform(lddat, y = rlaplace(nn, loc = 2, scale = exp(-1+1*x)))
coef(vglm(y ~ x, laplace(iloc = .2, imethod = 2, zero = 1), lddat,
trace = TRUE), matrix = TRUE)
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 15:40:18
