R语言 VGAM包 cratio()函数中文帮助文档(中英文对照)

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cratio(VGAM)
cratio()所属R语言包：VGAM

                                         Ordinal Regression with Continuation Ratios
                                         序回归与延续比率

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Fits a continuation ratio logit/probit/cloglog/cauchit/... regression model to an ordered (preferably) factor response.
适合的延续比罗吉特/机率/ cloglog / cauchit / ...回归模型的有序（最好）因子反应。


用法----------Usage----------


cratio(link = "logit", earg = list(),
       parallel = FALSE, reverse = FALSE, zero = NULL,
       whitespace = FALSE)



参数----------Arguments----------

参数：link
Link function applied to the M continuation ratio probabilities. See Links for more choices.  
Link功能M延续比的概率。见Links更多的选择。


参数：earg
List. Extra argument for the link function. See earg in Links for general information.  
列表。额外的参数的链接功能。见earg中Links的一般信息。


参数：parallel
A logical, or formula specifying which terms have equal/unequal coefficients.  
一个逻辑，或指定的条款有平等/不平等系数，公式。


参数：reverse
Logical. By default, the continuation ratios used are eta_j = logit(P[Y>j|Y>=j]) for j=1,&hellip;,M. If reverse is TRUE, then eta_j=logit(P[Y<j+1|Y<=j+1]) will be used.  
逻辑。默认情况下，延续比例是eta_j = logit(P[Y>j|Y>=j])j=1,&hellip;,M。如果reverseTRUE，那么eta_j=logit(P[Y<j+1|Y<=j+1])使用。


参数：zero
An integer-valued vector specifying which linear/additive predictors are modelled as intercepts only. The values must be from the set {1,2,...,M}. The default value means none are modelled as intercept-only terms.  
指定一个整数值向量线性/添加剂的预测模型仅作为拦截。这些值必须是集合{1,2，...，M}。默认值是指没有被建模为仅截距。


参数：whitespace
See CommonVGAMffArguments for information.  
见CommonVGAMffArguments的信息。


Details

详细信息----------Details----------

In this help file the response Y is assumed to be a factor with ordered values 1,2,&hellip;,M+1, so that M is the number of linear/additive predictors eta_j.
本帮助文件中的响应Y被认为是一个因素，有序值1,2,&hellip;,M+1，使M是线性/添加剂预测eta_j。

There are a number of definitions for the continuation ratio in the literature. To make life easier, in the VGAM package, we use continuation ratios and stopping ratios (see sratio).  Stopping ratios deal with quantities such as logit(P[Y=j|Y>=j]).
用于继续比在文献中有许多的定义。为了使生活更轻松，VGAM包，我们使用的延续比例和停止比率（见sratio，）。停止比例处理数量，如logit(P[Y=j|Y>=j])。


值----------Value----------

An object of class "vglmff" (see vglmff-class). The object is used by modelling functions such as vglm, rrvglm and vgam.
类的一个对象"vglmff"（见vglmff-class）。该对象被用于建模功能，如vglm，rrvglm和vgam。


警告----------Warning ----------

No check is made to verify that the response is ordinal; see ordered.
不进行任何检查来验证的响应顺序; ordered。


注意----------Note----------

The response should be either a matrix of counts (with row sums that are all positive), or a factor. In both cases, the y slot returned by vglm/vgam/rrvglm is the matrix of counts.
该反应应该是一个矩阵的计数（与行的款项都是正面），或一个因素。在这两种情况下，y返回vglm插槽/vgam/rrvglm是矩阵的计数。

For a nominal (unordered) factor response, the multinomial logit model (multinomial) is more appropriate.
对于标称值（无序的）因素的反应，多项式Logit模型（multinomial）是比较合适的。

Here is an example of the usage of the parallel argument. If there are covariates x1, x2 and x3, then parallel = TRUE ~ x1 + x2 -1 and parallel = FALSE ~ x3 are equivalent. This would constrain the regression coefficients for x1 and x2 to be equal; those of the intercepts and x3 would be different.
下面是一个例子parallel参数的使用。如果有协变量x1，x2和x3，那么parallel = TRUE ~ x1 + x2 -1和parallel = FALSE ~ x3是等效的。这将限制的回归系数x1和x2是相等的;的拦截和x3会有所不同。


（作者）----------Author(s)----------


Thomas W. Yee



参考文献----------References----------

Categorical Data Analysis, 2nd ed. New York: Wiley.
Analyzing Categorical Data, New York: Springer-Verlag.
Generalized Linear Models, 2nd ed. London: Chapman &amp; Hall.
The <code>VGAM</code> package for categorical data analysis. Journal of Statistical Software, 32, 1&ndash;34. http://www.jstatsoft.org/v32/i10/.
http://www.stat.auckland.ac.nz/~yee contains further information and examples.

参见----------See Also----------

sratio, acat, cumulative, multinomial, pneumo, logit, probit, cloglog, cauchit.
sratio，acat，cumulative，multinomial，pneumo，logit，probit，cloglog，cauchit。


实例----------Examples----------


pneumo = transform(pneumo, let = log(exposure.time))
(fit = vglm(cbind(normal, mild, severe) ~ let,
            cratio(parallel = TRUE), pneumo))
coef(fit, matrix = TRUE)
constraints(fit)
predict(fit)
predict(fit, untransform = TRUE)

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


注：
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