How can I predict values in factorial experiments (2^k) with centre points in R?

Question

How can I predict values in factorial experiments with centre points in R using FrF2 package with the predict function or using the broom package?

My code:

library(FrF2)
plan.person = FrF2(nfactors = 5, resolution = 5, replications = 2,
               ncenter = 1, randomize = FALSE,
               factor.names = list(
                 A = c(8, 5),
                 B = c(70, 30),
                 C = c(0.5, 0),
                 D = c(1000, 700),
                 E = c(70, 10)))

resp  <- c(84.55, 66.34, -1, 69.18, 73.01, 64.52, 0.73, 47.61, 68.18, 59.87, 
       26, 72.57, 78.08, 73.81, 26, 59.38, 71.41, 88.64, 64.92, 4, 68.81, 
       80, 69.66, -1.36, 54.50, 79.24, 78.53, -1, 72.63, 89.97, 87.98, 
       -11, 65.68, 82.46)

newplan <- add.response(design = plan.person, response = resp)

model <- lm(newplan, use.center = T)
# summary(model)

d <- within(newplan, {
  A <- as.numeric(as.character(A))
  B <- as.numeric(as.character(B))
  C <- as.numeric(as.character(C))
  D <- as.numeric(as.character(D))
  E <- as.numeric(as.character(E)) })

A = seq(5, 8, 1)
B = seq(30, 70, length.out = length(A))
C = seq(0, 0.5, length.out = length(A))
D = seq(700, 1000, length.out = length(A))
E = seq(10, 70, length.out = length(A))

data <- expand.grid(A = A, B = B,
                C = C, D = D,
                E = E)  

dados$p <- predict(model, newdata=data)

Because of the center point the following message appears.

Error in model.frame.default (Terms, newdata, na.action = na.action, xlev = object $ xlevels): lengths of variables differ (found in 'center')

Tarssio Barreto Tarssio Barreto · Accepted Answer · 2018-06-29T21:06:15

If you remove the central value, you can this after model <- lm(newplan, use.center = T):

1- Filter the pvalues < 0.05

coe <- broom::tidy(model) %>% 
  slice(-7) %>%   #remove center
  filter(p.value < 0.05)   

m_beta <- coe$estimate

2 - Do a grid:

A = seq(5, 8, 0.5)
B = seq(30, 70, length.out = length(A))

exp <- expand.grid(A = A, B = B) %>% 
  mutate(bo = as.numeric(1)) %>% 
  mutate(ult = A*B) %>% 
  select(bo, A, B, ult) %>% 
  as.matrix()

3: Do a Regression:

reg <- t(m_beta %*% t(exp)) 

exp <- cbind(exp, reg) %>% 
  as.data.frame() %>% 
  rename(reg = V5)

But I believe this only solves the computational problem or simplifies it. I believe linear regression should be redone as well. But with this code you can explore and see what other errors exist.

How can I predict values in factorial experiments (2^k) with centre points in R?

2 Answers