我想查看与某个对象类关联的所有方法的列表。例如。如果我看到某个模型拟合例程返回类“foo”的对象，我想知道包（或任何其他包）是否已定义方法，如simulate.foo，update.foo，{ {1}}，coef.foo等。我该怎么做？
我知道print.foo解决了反问题（假设是S3类），但显然我不想搜索已定义methods函数的每个对象以查明是否我感兴趣的课程有一个。我可能在这里忘记了一些非常简单的事情。谢谢！
（理想情况下，看到S3和S4类的解决方案会很好）。
更新：理想情况下，解决方案应该显示隐藏的方法，就像print函数一样。例如，methods显示：
methods("simulate")因此，在查询与> methods("simulate")
[1] simulate.lm*
类关联的方法时，我们希望恢复此模拟方法。
答案 0 :(得分：6)
我是傻瓜，还是methods(class="foo")你想要的（对于S3方法）???
methods(class="lm")
## [1] add1.lm* alias.lm* anova.lm case.names.lm*
## [5] confint.lm* cooks.distance.lm* deviance.lm* dfbeta.lm*
## [9] dfbetas.lm* drop1.lm* dummy.coef.lm* effects.lm*
## [13] extractAIC.lm* family.lm* formula.lm* hatvalues.lm
## [17] influence.lm* kappa.lm labels.lm* logLik.lm*
## [21] model.frame.lm model.matrix.lm nobs.lm* plot.lm
## [25] predict.lm print.lm proj.lm* qr.lm*
## [29] residuals.lm rstandard.lm rstudent.lm simulate.lm*
## [33] summary.lm variable.names.lm* vcov.lm*
##
## Non-visible functions are asterisked
showMethods适用于S4课程（摘自@JoshO'Brien现已删除的答案，供参考）：
library(sp)
showMethods(classes="SpatialPolygons")
## Function: [ (package base)
## x="SpatialPolygons"
##
## Function: addAttrToGeom (package sp)
## x="SpatialPolygons", y="data.frame"
##
## Function: coerce (package methods)
## from="GridTopology", to="SpatialPolygons"
## from="SpatialGrid", to="SpatialPolygons"
## from="SpatialPixels", to="SpatialPolygons"
## from="SpatialPolygons", to="SpatialLines"
## from="SpatialPolygons", to="SpatialPolygonsDataFrame"
##
## Function: coordinates (package sp)
## obj="SpatialPolygons"
##
## Function: coordnames (package sp)
## x="SpatialPolygons"
##
## Function: coordnames<- (package sp)
## x="SpatialPolygons", value="character"
##
## Function: over (package sp)
## x="SpatialGrid", y="SpatialPolygons"
## x="SpatialPoints", y="SpatialPolygons"
## x="SpatialPolygons", y="SpatialGrid"
## x="SpatialPolygons", y="SpatialGridDataFrame"
## x="SpatialPolygons", y="SpatialPoints"
## x="SpatialPolygons", y="SpatialPointsDataFrame"
##
## Function: overlay (package sp)
## x="SpatialGridDataFrame", y="SpatialPolygons"
## x="SpatialGrid", y="SpatialPolygons"
## x="SpatialPointsDataFrame", y="SpatialPolygons"
## x="SpatialPoints", y="SpatialPolygons"
## x="SpatialPolygons", y="SpatialGrid"
## x="SpatialPolygons", y="SpatialPoints"
##
## Function: plot (package graphics)
## x="SpatialPolygons", y="missing"
##
## Function: polygons (package sp)
## obj="SpatialPolygons"
##
## Function: polygons<- (package sp)
## object="data.frame", value="SpatialPolygons"
##
## Function: recenter (package sp)
## obj="SpatialPolygons"
##
## Function: spChFIDs (package sp)
## obj="SpatialPolygons", x="character"
##
## Function: spsample (package sp)
## x="SpatialPolygons"
答案 1 :(得分：4)
以下示例使用.lm作为apropos内的正则表达式模式，而不是无效地搜索.foo：
> apropos("\\.lm")
[1] "anova.lm" "anova.lmlist" "hatvalues.lm" "kappa.lm" "model.frame.lm" "model.matrix.lm"
[7] "panel.lmline" "plot.lm" "predict.lm" "prepanel.lmline" "print.lm" "residuals.lm"
[13] "rstandard.lm" "rstudent.lm" "summary.lm"
还有一些以“lm”开头的方法。所以你可能也想要那些：
> apropos("lm\\.")
[1] ".__C__anova.glm.null" ".__C__glm.null" "glm.control" "glm.convert"
[5] "glm.fit" "glm.nb" "lm.fit" "lm.fit.qr.bare"
[9] "lm.gls" "lm.influence" "lm.pfit" "lm.ridge"
[13] "lm.wfit"
如果你想放弃“glm”。方法使用更受限制的正则表达式：
> apropos("^lm\\.")
[1] "lm.fit" "lm.fit.qr.bare" "lm.gls" "lm.influence" "lm.pfit" "lm.ridge"
[7] "lm.wfit"
答案 2 :(得分：2)
对于S3情况，methods为此具有参数class：
> methods(class="lm")
[1] add1.lm* alias.lm* anova.lm case.names.lm*
[5] confint.lm* cooks.distance.lm* deviance.lm* dfbeta.lm*
[9] dfbetas.lm* drop1.lm* dummy.coef.lm* effects.lm*
[13] extractAIC.lm* family.lm* formula.lm* hatvalues.lm
[17] influence.lm* kappa.lm labels.lm* logLik.lm*
[21] model.frame.lm model.matrix.lm nobs.lm* plot.lm
[25] predict.lm print.lm proj.lm* qr.lm*
[29] residuals.lm rstandard.lm rstudent.lm simulate.lm*
[33] summary.lm variable.names.lm* vcov.lm*