multinom(nnet)
multinom()所属R语言包：nnet
Fit Multinomial Log-linear Models
符合多项对数线性模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Fits multinomial log-linear models via neural networks.
适用于多项对数线性模型，通过神经网络。
用法----------Usage----------
multinom(formula, data, weights, subset, na.action,
contrasts = NULL, Hess = FALSE, summ = 0, censored = FALSE,
model = FALSE, ...)
参数----------Arguments----------
参数：formula
a formula expression as for regression models, of the form response ~ predictors. The response should be a factor or a matrix with K columns, which will be interpreted as counts for each of K classes. A log-linear model is fitted, with coefficients zero for the first class. An offset can be included: it should be a numeric matrix with K columns if the response is either a matrix with K columns or a factor with K > 2 classes, or a numeric vector for a response factor with 2 levels. See the documentation of formula() for other details.
回归模型，公式表达的形式response ~ predictors。该反应应该是与K列，每个K类的计数将被解释为一个因素或矩阵。对数线性模型拟合的系数为零，第一类。的偏移量，可以包括：如果响应是与K列的矩阵或与K> 2类的因素，或2级的响应因子与一个数值向量，它应该是一个数字与K列的矩阵。请参阅文档formula()其他细节。
参数：data
an optional data frame in which to interpret the variables occurring in formula.
一个可选的数据框，其中解释的变量发生在formula。
参数：weights
optional case weights in fitting.
可选的情况下，权重装修。
参数：subset
expression saying which subset of the rows of the data should be used in the fit. All observations are included by default.
表达说应在适合使用的哪个子集的行的数据。默认情况下，所有的观测。
参数：na.action
a function to filter missing data.
一个函数来筛选丢失的数据。
参数：contrasts
a list of contrasts to be used for some or all of the factors appearing as variables in the model formula.
要用于出现的因素作为模型公式中的变量的一些或所有的列表对比。
参数：Hess
logical for whether the Hessian (the observed/expected information matrix) should be returned.
逻辑是否黑森州（观察/预期的信息矩阵）应返回。
参数：summ
integer; if non-zero summarize by deleting duplicate rows and adjust weights. Methods 1 and 2 differ in speed (2 uses C); method 3 also combines rows with the same X and different Y, which changes the baseline for the deviance.
整数，如果通过删除重复行的非零总结和调整权重。方法1和2的速度不同（2使用C）;方法3还结合行使用相同的X和Y，改变基线的偏差。
参数：censored
If Y is a matrix with K > 2 columns, interpret the entries as one for possible classes, zero for impossible classes, rather than as counts.
如果Y是一个矩阵K > 2列，作为一个可能的类，零不可能类的条目解释，而不是计数。
参数：model
logical. If true, the model frame is saved as component model of the returned object.
逻辑。如果为true，该模型帧保存为组件model返回的对象。
参数：...
additional arguments for nnet </table>
附加参数为nnet</ TABLE>
Details
详细信息----------Details----------
multinom calls nnet. The variables on the rhs of the formula should be roughly scaled to [0,1] or the fit will be slow or may not converge at all.
multinomnnet。公式右边的变量大致应扩展到[0,1]或适合将是缓慢的，或不收敛。
值----------Value----------
A nnet object with additional components:
Annet对象与其他组件：
参数：deviance
the residual deviance, compared to the full saturated model (that explains individual observations exactly). Also, minus twice log-likelihood.
剩余偏差，相比全饱和模型（即完全解释个人的观察）。此外，减去两倍的对数似然。
参数：edf
the (effective) number of degrees of freedom used by the model
（有效）的自由度数模型所使用的
参数：AIC
the AIC for this fit.
这适合AIC。
参数：Hessian
(if Hess is true).
（Hess如果是真实的）。
参数：model
(if model is true). </table>
（model如果是真实的）。 </ TABLE>
参考文献----------References----------
Modern Applied Statistics with S. Fourth edition. Springer.
参见----------See Also----------
nnet
nnet
实例----------Examples----------
options(contrasts = c("contr.treatment", "contr.poly"))
library(MASS)
example(birthwt)
(bwt.mu <- multinom(low ~ ., bwt))
## Not run: Call:[＃不运行：检测：]
multinom(formula = low ~ ., data = bwt)
Coefficients:
(Intercept) age lwt raceblack raceother
0.823477 -0.03724311 -0.01565475 1.192371 0.7406606
smoke ptd ht ui ftv1 ftv2+
0.7555234 1.343648 1.913213 0.6802007 -0.4363238 0.1789888
Residual Deviance: 195.4755
AIC: 217.4755
## 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 2012-9-23 20:01:16
