polr(MASS)
polr()所属R语言包：MASS
Ordered Logistic or Probit Regression
有序的后勤或probit回归
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Fits a logistic or probit regression model to an ordered factor response. The default logistic case is proportional odds logistic regression, after which the function is named.
适合一个有序的因子响应的物流或probit回归模型。默认物流的情况下是成正比的赔率logistic回归后，该函数被命名为。
用法----------Usage----------
polr(formula, data, weights, start, ..., subset, na.action,
contrasts = NULL, Hess = FALSE, model = TRUE,
method = c("logistic", "probit", "cloglog", "cauchit"))
参数----------Arguments----------
参数：formula
a formula expression as for regression models, of the form response ~ predictors. The response should be a factor (preferably an ordered factor), which will be interpreted as an ordinal response, with levels ordered as in the factor. The model must have an intercept: attempts to remove one will lead to a warning and be ignored. An offset may be used. See the documentation of formula for other details.
作为回归模型公式表达形式response ~ predictors。响应应该是一个因素（最好是一个有序的因素），下令因子的水平，这将被解释为序反应。模型必须有一个拦截：将导致试图删除一个警告被忽略。可以用一个偏移。看到formula其他细节的文件。
参数：data
an optional data frame in which to interpret the variables occurring in formula.
在解释变量发生在formula可选的数据框。
参数：weights
optional case weights in fitting. Default to 1.
接头可选的情况下重量。默认为1。
参数：start
initial values for the parameters. This is in the format c(coefficients, zeta): see the Values section.
为参数的初始值。这是在格式c(coefficients, zeta)：看到值“部分。
参数：...
additional arguments to be passed to optim, most often a control argument.
额外的参数将被传递给optim，最常见的是control参数。
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，应在适当使用数据行的一个子集。所有的意见，包括默认情况下。
参数：na.action
a function to filter missing data.
一个函数来过滤丢失的数据。
参数：contrasts
a list of contrasts to be used for some or all of the factors appearing as variables in the model formula.
对比的名单将部分或全部的模型公式中的变量出现的因素。
参数：Hess
logical for whether the Hessian (the observed information matrix) should be returned. Use this if you intend to call summary or vcov on the fit.
黑森州（观测信息矩阵）是否应退还的逻辑。如果你打算叫summary或vcov适合使用此。
参数：model
logical for whether the model matrix should be returned.
逻辑模型矩阵是否应退还。
参数：method
logistic or probit or complementary log-log or cauchit (corresponding to a Cauchy latent variable).
后勤或Probit或互补的日志记录或cauchit（相应的到柯西潜变量）。
Details
详情----------Details----------
This model is what Agresti (2002) calls a cumulative link model. The basic interpretation is as a coarsened version of a latent variable Y_i which has a logistic or normal or extreme-value or Cauchy distribution with scale parameter one and a linear model for the mean. The ordered factor which is observed is which bin Y_i falls into with breakpoints
这种模式是什么Agresti（2002）累积的链接模式。作为一个潜变量的粗化版本的基本解释是Y_i其中有一个尺度参数和一个线性模型平均后勤或正常或极端值或柯西分布。观察有序的因素是其中的binY_i落入断点
This leads to the model
这导致模型
with logit replaced by probit for a normal latent variable, and eta being the linear predictor, a linear function of the explanatory variables (with no intercept). Note that it is quite common for other software to use the opposite sign for eta (and hence the coefficients beta).
与的罗吉特取代了正常的潜变量的概率，并eta线性预测，线性函数的解释变量（没有拦截）。请注意，这是其他软件的使用相当普遍的符号相反eta（因此系数beta）。
In the logistic case, the left-hand side of the last display is the log odds of category k or less, and since these are log odds which differ only by a constant for different k, the odds are proportional. Hence the term proportional odds logistic regression.
在物流的情况下，最后显示的左侧是类别的日志赔率k或更少，因为这些日志赔率仅相差一个常数不同k，胜算成正比。因此，长期比例胜算logistic回归。
In the complementary log-log case, we have a proportional hazards model for grouped survival times.
在互补的日志记录的情况下，我们有一个分组的存活时间的比例风险模型。
There are methods for the standard model-fitting functions, including predict, summary, vcov, anova, model.frame and an extractAIC method for use with stepAIC (and step. There are also profile and confint methods.
有标准模型拟合功能，包括predict，summary，vcov，anova，model.frame和extractAIC方法的方法使用stepAIC（step还有profile和confint方法。
值----------Value----------
A object of class "polr". This has components
一类"polr"的对象。这有组件
参数：coefficients
the coefficients of the linear predictor, which has no intercept.
的线性预测系数，其中有没有拦截。
参数：zeta
the intercepts for the class boundaries.
阶级界限的拦截。
参数：deviance
the residual deviance.
剩余的越轨行为。
参数：fitted.values
a matrix, with a column for each level of the response.
与每个响应级别的列的矩阵。
参数：lev
the names of the response levels.
响应级别的名称。
参数：terms
the terms structure describing the model.
terms结构描述模型。
参数：df.residual
the number of residual degrees of freedoms, calculated using the weights.
剩余的自由程度，使用权重计算。
参数：edf
the (effective) number of degrees of freedom used by the model
（有效）的自由度模型
参数：n, nobs
the (effective) number of observations, calculated using the weights. (nobs is for use by stepAIC.
观察（有效），使用权重计算。 （nobs是stepAIC。
参数：call
the matched call.
匹配的呼叫。
参数：method
the matched method used.
用匹配的方法。
参数：convergence
the convergence code returned by optim.
optim返回的衔接代码。
参数：niter
the number of function and gradient evaluations used by optim.
由optim使用功能和梯度评价。
参数：lp
the linear predictor (including any offset).
线性预测（包括任何偏移）。
参数：Hessian
(if Hess is true). Note that this is a numerical approximation derived from the optimization proces.
（Hess如果是真实的）。请注意，这是一个优化议事录所得的数值逼近。
参数：model
(if model is true).
（model如果是真实的）。
注意----------Note----------
The vcov method uses the approximate Hessian: for reliable results the model matrix should be sensibly scaled with all columns having range the order of one.
vcov方法使用近似的Hessian：可靠的结果，应理智与所有列有范围的一阶缩放模型矩阵。
参考文献----------References----------
Modern Applied Statistics with S. Fourth edition. Springer.
参见----------See Also----------
optim, glm, multinom.
optim，glm，multinom。
举例----------Examples----------
options(contrasts = c("contr.treatment", "contr.poly"))
house.plr <- polr(Sat ~ Infl + Type + Cont, weights = Freq, data = housing)
house.plr
summary(house.plr, digits = 3)
## slightly worse fit from[＃略有适合从]
summary(update(house.plr, method = "probit", Hess = TRUE), digits = 3)
## although it is not really appropriate, can fit[＃虽然它是不是真的合适，可以容纳]
summary(update(house.plr, method = "cloglog", Hess = TRUE), digits = 3)
predict(house.plr, housing, type = "p")
addterm(house.plr, ~.^2, test = "Chisq")
house.plr2 <- stepAIC(house.plr, ~.^2)
house.plr2$anova
anova(house.plr, house.plr2)
house.plr <- update(house.plr, Hess=TRUE)
pr <- profile(house.plr)
confint(pr)
plot(pr)
pairs(pr)
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 2012-2-16 20:49:21
