msn.mle(sn)
msn.mle()所属R语言包：sn
Maximum likelihood estimation for a multivariate skew-normal distribution
一个多变量偏斜正态分布的最大似然估计
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Fits a multivariate skew-normal (MSN) distribution to data, or fits a linear regression model with multivariate skew-normal errors, using maximum likelihood estimation.
适用于多变量歪斜正常（MSN）分布的数据，或符合一元线性回归模型多元歪斜正常的错误，用最大似然估计。
用法----------Usage----------
msn.mle(X, y, freq, start, trace=FALSE,
algorithm=c("nlminb", "Nelder-Mead", "BFGS", "CG", "SANN"),
control=list())
参数----------Arguments----------
参数：y
a matrix or a vector. If y is a matrix, rows refer to observations, and columns to components of the multivariate distribution. If y is a vector, it is converted to a one-column matrix, and a scalar skew-normal distribution is fitted.
一个矩阵或矢量。如果y是一个矩阵，行观察，和多变量分布列的组成部分。如果y是一个矢量，它被转换到一个列的矩阵，和一个标量歪斜正态分布嵌合。
参数：X
a matrix of covariate values. If missing, a one-column matrix of 1's is created; otherwise, it must have the same number of rows of y, and it must include a column of 1's if an intercept term is required.
矩阵的协变量值。如果缺少，矩阵中1的一列被创建，否则，它必须有相同数量的行y，而且它必须包含一列的“1”，如果需要截距项。
参数：freq
a vector of weights. If missing, a vector of 1's is created; otherwise it must have length equal to the number of rows of y.
的权重的矢量。如果缺少，创建的向量1的，否则，它必须有y的数量的行的长度相等。
参数：start
a list containing the components beta,Omega, alpha, of the type described below. The dp component of the returned list from a previous call has the required format.
的列表中包含的组件beta，Omega，alpha，下面所描述的类型。 dp从以前的调用返回的列表的组成部分所需的格式。
参数：trace
logical value which controls printing of the algorithm convergence. If trace=TRUE, details are printed. Default value is FALSE.
逻辑控制打印算法的收敛值。如果trace=TRUE，细节被打印出来。默认值为FALSE。
参数：algorithm
a character string which selects the numerical optimization procedure used to maximize the log-likelihood function. If this string is set equal to "nlminb", then this function is called; in all other cases, optim is called, with method set equal to the given string. Default value is "nlminb".
一个字符串，选择的数值优化程序，用于使对数似然函数最大化。如果该字符串等于"nlminb"，那么这个函数将被调用;在所有其他情况下，optim被称为，method设置为等于给定的字符串。默认值为"nlminb"。
参数：control
this parameter is passed to the optimizer selected via algorithm; see the documentation of nlminb or optim for its usage. </table>
通过此参数的优化选择通过algorithm; nlminb或optim其使用的文档。 </ TABLE>
Details
详细信息----------Details----------
The parameter freq is intended for use with grouped data, setting the values of y equal to the central values of the cells; in this case the resulting estimate is an approximation to the exact maximum likelihood estimate. If freq is not set, exact maximum likelihood estimation is performed.
参数freq被用于与分组数据一起使用，设置y等于单元的中心值的值，在这种情况下，将所得的估计是一个近似的精确的最大似然估计。 freq如果没有设置，精确极大似然估计。
The working parameter used in the maximization stage is c(beta,alpha/omega), since a profile "deviance" -2*loglikelihood for this parameter is actually used; see Azzalini and Capitanio (1999, section 6.1) for details. The selected optimizer (nlminb or optim) is called, supplying the gradient of the profile deviance. In case the optimizer is optim), the gradient may or may not be used, depending on which specific method has been selected.
在最大化阶段的工作参数是c(beta,alpha/omega)，因为配置文件的“越轨行为”-2*loglikelihood，此参数的实际使用Azzalini和卡皮塔尼奥（1999年，第6.1节）的详细信息。所选择的优化器（nlminb或optim）被称为提供的档案偏差的梯度。的情况下，优化器是optim），渐变可能会或可能不会被使用，这取决于特定的方法已被选定。
The function can take a vector y as input; however the use of sn.mle is recommended in the scalar case.
该功能可以采取一个向量y输入，但是在标量情况下，推荐使用sn.mle。
值----------Value----------
A list containing the following components:
一个列表，其中包含以下组件：
<table summary="R valueblock"> <tr valign="top"><td>call</td> <td> a string containing the calling statement. </td></tr> <tr valign="top"><td>dp</td> <td> a list containing terms named beta, Omega, alpha, where beta is a matrix of regression coefficients with dim(beta)=c(nrow(X),ncol(y)), Omega is a covariance matrix of order ncol(y), alpha is a vector of shape parameters of length ncol(y). </td></tr> <tr valign="top"><td>se</td> <td> a list containing the components beta, alpha, info. Here, beta and alpha are the standard errors for the corresponding point estimates; info is the observed information matrix for the working parameter, as explained below. </td></tr> <tr valign="top"><td>algorithm</td> <td> the list returned by the chose optimizer, either nlminb or optim, plus an item with the name of the selected algorithm; see the documentation of either nlminb or optim for explanation of the other components. </td></tr></table>
<table summary="R valueblock"> <tr valign="top"> <TD>call</ TD> <td>一个字符串，其中包含调用语句。 </ TD> </ TR> <tr valign="top"> <TD> dp</ TD> <td>一个列表，其中包含术语命名为beta，Omega，alpha其中beta是一个矩阵的回归系数与dim(beta)=c(nrow(X),ncol(y))，Omega的协方差矩阵为了ncol(y)，alpha是一个矢量形状参数的长度ncol(y)。 </ TD> </ TR> <tr valign="top"> <TD> se</ TD> <td>一个列表，其中包含的组件beta，alpha，info。在这里，beta和alpha的对应点的标准误差的估计;info是观察到的信息矩阵的工作参数，如下面解释。 </ TD> </ TR> <tr valign="top"> <TD>algorithm </ TD> <TD>列表中返回所选择的优化，无论是nlminb或optim ，加上一个资料与name选定的算法;看到的文档的任nlminb或optim用于说明的其他组件。 </ TD> </ TR> </ TABLE>
背景----------Background----------
The multivariate skew-normal distribution is discussed by Azzalini and Dalla Valle (1996); the (Omega,alpha) parametrization adopted here is the one of Azzalini and Capitanio (1999).
的多元歪斜正态分布讨论由Azzalini和达拉瓦莱达奥（1996年）;这里通过(Omega,alpha)参数化是一项Azzalini和卡皮塔尼奥（1999）。
参考文献----------References----------
Azzalini, A. and Dalla Valle, A. (1996). The multivariate skew-normal distribution. Biometrika 83, 715–726.
Azzalini, A. and Capitanio, A. (1999). Statistical applications of the multivariate skew-normal distribution. J.Roy.Statist.Soc. B 61, 579–602.
参见----------See Also----------
dmsn,msn.fit, nlminb, optim
dmsn，msn.fit，nlminb，optim
实例----------Examples----------
data(ais, package="sn")
attach(ais)
# a simple-sample case[一个简单的样品的情况下，]
a <- msn.mle(y=cbind(Ht,Wt))
#[]
# a regression case:[一个回归的情况下：]
b <- msn.mle(X=cbind(1,Ht,Wt), y=ssf)
b1 <- msn.mle(X=cbind(1,Ht,Wt), y=ssf, algorithm="Nelder-Mead")
b2 <- msn.mle(X=cbind(1,Ht,Wt), y=ssf, start=b1$dp)
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 2012-9-30 11:19:20
