Dear R users,
I have a large data set which includes data from 300 cities. I want to run
a biviriate regression for each city and record the coefficient and the
adjusted R square.
For example, in the following, I have 10 cities represented by numbers from
1 to 10:
x = cumsum(c(0, runif(999, -1, +1)))
y = cumsum(c(0, runif(999, -1, +1)))
city = rep(1:10,each=100)
data<-data.frame(cbind(x,y,city))
I can manually run regressions for each city:
fit_city1 <- lm(y ~ x,data=subset(data,data$city==1))
summary(fit_city1)
Obvious, it is very tedious to run 300 regressions. I wonder if there is a
quicker way to do this. Use for loop? what I want to see is something like
this:
City Coefficient Adjusted R square
1 -0.05 0.36
2 -0.12 0.20
3 -0.05 0.32
.....
Any advice is appreciated!
Gary
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