基于R中的其他变量模拟变量

发布于 2025-01-23 23:16:07 字数 176 浏览 1 评论 0原文

我希望模拟一组与模拟数值变量相关的分类变量。更具体地说，我具有可变的age，其定义为：age＆lt; - rnorm（n = 1000，平均= 35，sd = 9），我希望模拟另一个变量类，其中更高的年龄使更高的类。谁能向我指向正确的方向？提前致谢！

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秋日私语 2025-01-30 23:16:07

我知道的是，如果a与b相关，则表示a和b是线性相关的。因此，a可以用b的线性函数表示。为了生成随机变量，应添加随机噪声。

这是这样做的一种方法：

set.seed(1)
age <- rnorm(n=10, mean=35, sd =9)
beta <- runif(1, min = 1, max = 5) # or any other finite min and max values, can be positive or negative, but in your case should be positive.
class <- beta*age + rnorm(length(age), mean = 0, sd = 2) # or any other mean and sd values

# Check correlation between age and class
cor(age, class)
#[1] 0.9994416

# Check if higher age makes for higher class
data.frame(sort(age), sort(class))

   sort.age. sort.class.
1   27.47934    129.6408
2   27.61578    131.3707
3   29.36192    137.5428
4   32.25150    152.3856
5   36.65279    171.3957
6   37.96557    179.0890
7   39.38686    184.8634
8   40.18203    187.9404
9   41.64492    198.2192
10  49.35753    233.2981

What I understand is that if a correlates with b, it means a and b are linearly related. So, a can be represented by a linear function of b. To generate random variables, a random noise should be added.

Here is one way of doing that:

set.seed(1)
age <- rnorm(n=10, mean=35, sd =9)
beta <- runif(1, min = 1, max = 5) # or any other finite min and max values, can be positive or negative, but in your case should be positive.
class <- beta*age + rnorm(length(age), mean = 0, sd = 2) # or any other mean and sd values

# Check correlation between age and class
cor(age, class)
#[1] 0.9994416

# Check if higher age makes for higher class
data.frame(sort(age), sort(class))

   sort.age. sort.class.
1   27.47934    129.6408
2   27.61578    131.3707
3   29.36192    137.5428
4   32.25150    152.3856
5   36.65279    171.3957
6   37.96557    179.0890
7   39.38686    184.8634
8   40.18203    187.9404
9   41.64492    198.2192
10  49.35753    233.2981

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