I have this data set that I will used for my model
set.seed(123)
x <- rnorm(100)
DF <- data.frame(x = x,
y = 4 + (1.5*x) + rnorm(100, sd = 2),
b = as.factor(round(abs(DF$x/3))),
c = as.factor(round(abs(DF$y/3)))
)
I was assigned to create a multiplicative model for them with a based 5 like this equation:
y=5*b(i)*c(i)
but the best that I can do is this one:
m1 <- lm(y ~ b*c, data = DF)
summary(m1)
This model is okay but I do want to remove the additive effect and just get the multiplicative model and I also replace the intercept with 5 and create difference coefficient for the first level of b and c.
Is there a way in R to do this task?
To fit the model without a constant use lm(y~b*c -1,...). Setting a fixed constant can be done by specifying the offset and not fitting the constant or by subtracting the known constant from the dependent variable and fitting a model with no constant.
set.seed(123)
x <- rnorm(100)
DF <- as.data.frame(cbind(x))
DF$y = 4 + (1.5*x) + rnorm(100, sd = 2)
DF$b = round(abs(DF$x/3))
DF$c = round(abs(DF$y/3))
DF$bc = DF$b*DF$c
m1 <- lm(y~ b*c, data=DF) # model w/ a constant
m2 <- lm(y~ b*c - 1, data=DF) # model w/o a constant
m3 <- lm(y~ b*c -1 + offset(rep(5,nrow(DF))), data=DF) # model w/ a constant of 5
m4 <- lm(y-5~ b*c -1, data=DF) # subtracting fixed constant from y's