extracting linear model coefficients into a vector within a loop

问题

I am trying to create sample of 200 linear model coefficients using a loop in R. As an end result, I want a vector containing the coefficients.

for (i in 1:200) {        
  smpl_5 <- population[sample(1:1000, 5), ]
  model_5 <- summary(lm(y~x, data=smpl_5))         
}

I can extract the coefficients easy enough, but I am having trouble outputting them into a vector within the loop. Any Suggestions?

回答1:

You can use replicate for this if you like. In your case, because the number of coefficients is identical for all models, it'll return an array as shown in the example below:

d <- data.frame(x=runif(1000))
d$y <- d$x * 0.123 + rnorm(1000, 0, 0.01)
coefs <- replicate(3, {
  xy <- d[sample(nrow(d), 100), ]
  coef(summary(lm(y~x, data=xy)))
})

coefs

# , , 1
# 
#                Estimate  Std. Error    t value     Pr(>|t|)
# (Intercept) 0.001361961 0.002091297  0.6512516 5.164083e-01
# x           0.121142447 0.003624717 33.4212114 2.235307e-55
# 
# , , 2
# 
#                Estimate  Std. Error  t value     Pr(>|t|)
# (Intercept) 0.003213314 0.001967050  1.63357 1.055579e-01
# x           0.118026828 0.003332906 35.41259 1.182027e-57
# 
# , , 3
# 
#                Estimate  Std. Error   t value     Pr(>|t|)
# (Intercept) 0.003366678 0.001990226  1.691606 9.389883e-02
# x           0.119408470 0.003370190 35.430783 1.128070e-57

Access particular elements with normal array indexing, e.g.:

coefs[, , 1] # return the coefs for the first model

#                Estimate  Std. Error    t value     Pr(>|t|)
# (Intercept) 0.001361961 0.002091297  0.6512516 5.164083e-01
# x           0.121142447 0.003624717 33.4212114 2.235307e-55

So, for your problem, you could use:

replicate(200, { 
  smpl_5 <- population[sample(1:1000, 5), ]
  coef(summary(lm(y~x, data=smpl_5))) 
})

来源：https://stackoverflow.com/questions/26531278/extracting-linear-model-coefficients-into-a-vector-within-a-loop

标签

loops