How to plot interaction effects from extremely large data sets (esp. from rxGlm output)

Question

I am currenlty computing glm models off a huge data data set. Both glm and even speedglm take days to compute.

I currently have ar

Answer 1

If you can get the coefficients can't you just roll your own? This would not be a dataset size issue

# ex. data
n = 2000
dat <- data.frame( dv = sample(0:1, size = n, rep = TRUE), 
                   iv1 = sample(1:10, size = n, rep = TRUE),
                   iv2 = sample(1:10, size = n, rep = TRUE),
                   iv3 = sample(1:10, size = n, rep = TRUE),
                   iv4 = sample(0:10, size = n, rep = TRUE),
                   iv5 = as.factor(sample(0:1, size = n, rep = TRUE)),
                   x = sample(1:100, size = n, rep = TRUE),
                   y = as.factor(sample(0:1, size = n, rep = TRUE)),
                   ff1  = as.factor(sample(1:15, size = n, rep = TRUE)),
                   ff2  = as.factor(sample(1:100, size = n, rep = TRUE))
                   )

mod1 <- glm(formula = dv ~ 
                      iv1 + iv2 + iv3+ 
                      iv4 + iv5 +
                      x * y +
                      ff1  + ff2,
                    family = binomial(link = "probit"), data = dat)

# coefficients for x, y and their interaction
x1 <- coef(mod1)['x']
y1 <- coef(mod1)['y1']
xy <- coef(mod1)['x:y1']

x <- 1:100
a <- x1*x
b <- x1*x + y1 + xy*x

plot(a~x, type= 'line', col = 'red', xlim = c(0,max(x)), ylim = range(c(a, b)))
lines(b~x, col = 'blue')
legend('topright', c('y = 0', 'y = 1'), col = c('red', 'blue'))