[R] Time-varying correlation calculation

[Tim Hesterberg]

You can do this using an interaction of bs(time) and x, e.g.:

# Time-varying coefficient
x <- rnorm(100)
time <- ppoints(100)
y <- sin(time) + cos(time)*x + rnorm(100)/10

library("splines")
fit <- lm(y ~ bs(time, df=5) * x)
fit
# Plot estimated intercept vs time
plot(time, coef(fit)[1] + bs(time, df=5) %*% coef(fit)[2:6])
lines(time, sin(time))
# Plot estimated slope vs time
plot(time, coef(fit)[7] + bs(time, df=5) %*% coef(fit)[8:12])
lines(time, cos(time))

Thanks to Trevor Hastie for suggesting this approach, when
I made a similar query on S-news years ago.

Tim Hesterberg

>  I'm interested in getting a series of time-varying correlation, simply between two random variables.
>   
>  Could you please introduce a package to do this task?
>   
>  Thank you so much for any help.
>  Amir 

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