朱莉娅中的虚拟变量

问题描述

在R中，有很好的功能，可以对分类变量的每个级别使用虚拟变量运行回归.例如将R因子自动扩展为每个因子水平的1/0个指标变量的集合

In R there is nice functionality for running a regression with dummy variables for each level of a categorical variable. e.g. Automatically expanding an R factor into a collection of 1/0 indicator variables for every factor level

在朱莉娅(Julia)中有等效的方法吗?

Is there an equivalent way to do this in Julia.

x = randn(1000)
group = repmat(1:25 , 40)
groupMeans = randn(25)
y = 3*x + groupMeans[group]

data = DataFrame(x=x, y=y, g=group)
for i in levels(group)
    data[parse("I$i")] = data[:g] .== i
end
lm(y~x+I1+I2+I3+I4+I5+I6+I7+I8+I9+I10+
    I11+I12+I13+I14+I15+I16+I17+I18+I19+I20+
    I21+I22+I23+I24, data)

推荐答案

如果您使用DataFrames包，则在pool数据之后，其余的包将由您处理:

If you are using the DataFrames package, after you pool the data, the package will take care of the rest:

您可以在此处上查看其余文档. a>

You can see the rest of documentation on pooled data here

这篇关于朱莉娅中的虚拟变量的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！