如何改变点并添加回归（用R）一cloudplot？ [英] How to change points and add a regression to a cloudplot (using R)?

问题描述

要弄清楚什么我问我创建了一个简单的例子。第一步是创建一些数据：

To make clear what I'm asking I've created an easy example. Step one is to create some data:

gender <- factor(rep(c(1, 2), c(43, 41)), levels = c(1, 2),labels = c("male", "female"))
numberofdrugs <- rpois(84, 50) + 1
geneticvalue <- rpois(84,75)
death <- rpois(42,50) + 15
y <- data.frame(death, numberofdrugs, geneticvalue, gender)

因此​​，这些都是一些随机的日期合并为一个 data.frame 。因此，从这些日期，我想绘制的云，我可以的男性和女性，并在那里我加了两个简单的回归（一个为女性和一个用于男性）之间的差异。所以，我已经开始了，但我不能得到的地方，我想这一点。请看下面是我到目前为止，完成的：

So these are some random dates merged to one data.frame. So from these dates I'd like to plot a cloud where I can differ between the males and females and where I add two simple regressions (one for females and one for males). So I've started, but I couldn't get to the point where I want to be. Please see below what I've done so far:

require(lattice)
cloud(y$death~y$numberofdrugs*geneticvalue)

xmale <- subset(y, gender=="male")
xfemale <- subset(y, gender=="female")

death.lm.male <- lm(death~numberofdrugs+geneticvalue, data=xmale)
death.lm.female <- lm(death~numberofdrugs+geneticvalue, data=xfemale)

我怎样才能使不同的点进行男性或女性使用云命令（例如蓝色和粉红色的点，而不是仅仅蓝十字）的时候，我怎么能添加两个估计模型到云图？

How can I make different points for males or females when using the cloud command (for example blue and pink points instead of just blue crosses) and how can I add the two estimated models to the cloud graph?

任何想到的是AP preciated！感谢您的想法！

Any thought is appreciated! Thanks for your ideas!

推荐答案

回答第一个你的问题的一半，我怎样才能让不同的点进行男性或女性使用云命令（例如蓝色和粉红色点的时候insted的只是蓝十字）？

Answer to the first half of your question, "How can I make different points for males or females when using the cloud command (for example blue and pink points insted of just blue crosses)?"

 cloud( death ~ numberofdrugs*geneticvalue , groups=gender, data=y )

荟萃答案，这可能会涉及一些非三维可视化。也许你可以用格子或GGPLOT2将数据分割成小的倍数？它可能会更玉米prehensible和可能更容易添加回归结果

The meta-answer to this may involve some non-3d visualization. Perhaps you can use lattice or ggplot2 to split the data into small multiples? It will likely be more comprehensible and likely easier to add the regression results.

splom( ~ data.frame( death, numberofdrugs, geneticvalue ), groups=gender, data=y )

默认splom面板功能是panel.pairs，你可以有可能修改它添加回归线没有麻烦了巨大的金额。

The default splom panel function is panel.pairs, and you could likely modify it to add a regression line without an enormous amount of trouble.

GGPLOT2做回归剧情基质中很容易，但我不能得到的颜色来工作。

ggplot2 does regressions within the plot matrix easily, but I can't get the colors to work.

pm <- plotmatrix( y[ , 1:3], mapping = aes(color=death) )
pm + geom_smooth(method="lm")

最后，如果你真的想要做一个cloudplot与回归平面，这里有一个方法使用scatterplot3d包做。请注意，我改变了数据有更有趣的结构看：

And finally, if you really want to do a cloudplot with a regression plane, here's a way to do it using the scatterplot3d package. Note I changed the data to have a little more interesting structure to see:

numberofdrugs <- rpois( 84, 50 ) + 1
geneticvalue <- numberofdrugs + rpois( 84, 75 )
death <- geneticvalue + rpois( 42, 50 ) + 15
y <- data.frame( death, numberofdrugs, geneticvalue, gender )

library(scatterplot3d) 
pts <- as.numeric( as.factor(y$gender) ) + 4
s <-scatterplot3d( y$death, y$numberofdrugs, y$geneticvalue, pch=pts, type="p", highlight.3d=TRUE )
fit <- lm( y$death ~ y$numberofdrugs + y$geneticvalue )
s$plane3d(fit)

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