[英]Is the a way to regenerate data for 500 times?
library(MASS)
# set seed and create data vectors
#set.seed(98989) <- for replicating results of betas in 1-2 1-3
sample_size <- 200
sample_meanvector <- c(3, 4)
sample_covariance_matrix <- matrix(c(2, 1, 1, 2),
ncol = 2)
# create bivariate normal distribution
sample_distribution <- mvrnorm(n = sample_size,
mu = sample_meanvector,
Sigma = sample_covariance_matrix)
#Convert the datatype
df_sample_distribution <- as.data.frame(sample_distribution)
Is there a way to put this entire chunk of code in a loop and regenerate it for 500 times?有没有办法将整个代码块放入循环中并重新生成 500 次? Would be even better if i can store them somewhere.
如果我能把它们存放在某个地方就更好了。
You might use replicate()
你可以使用
replicate()
library(MASS)
out <- replicate(3, simplify = FALSE, {sample_size <- 200
sample_meanvector <- c(3, 4)
sample_covariance_matrix <- matrix(c(2, 1, 1, 2),
ncol = 2)
# create bivariate normal distribution
sample_distribution <- mvrnorm(n = sample_size,
mu = sample_meanvector,
Sigma = sample_covariance_matrix)
#Convert the datatype
df_sample_distribution <- as.data.frame(sample_distribution)
head(df_sample_distribution) # for shorter output
})
out
#> [[1]]
#> V1 V2
#> 1 3.195478 4.393699
#> 2 2.553590 5.065685
#> 3 2.822811 2.389559
#> 4 2.267116 4.076016
#> 5 1.659459 3.830608
#> 6 1.377554 4.009023
#>
#> [[2]]
#> V1 V2
#> 1 2.8850139 3.107203
#> 2 3.0313680 5.163229
#> 3 3.8649482 4.594017
#> 4 3.2747060 4.085805
#> 5 -0.1640264 3.628542
#> 6 3.6504855 4.747372
#>
#> [[3]]
#> V1 V2
#> 1 1.3230817 4.075396
#> 2 3.6049470 6.293968
#> 3 6.1211276 7.673592
#> 4 5.2955379 6.736665
#> 5 0.9032304 2.606501
#> 6 3.6034566 3.880563
Created on 2022-12-04 with reprex v2.0.2创建于 2022-12-04,使用reprex v2.0.2
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