Could anyone provides me guidance on how to use function (apply or map family) to find the best beta from each column used to calculate HOLT forecasting. Here is the data that has a total of two columns.
structure(list(T = c(6753L, 6763L, 6803L, 6806L, 6777L, 6799L,
6809L, 6832L, 6838L, 6831L, 6838L, 6807L, 6782L, 6809L, 6785L,
6766L, 6788L, 6704L, 6656L, 7093L, 7091L, 7100L, 7074L, 7047L,
7063L, 7070L, 7068L, 7054L, 7056L, 7067L, 7040L, 7027L, 7032L,
7055L, 7058L, 7051L, 7074L, 7109L, 7103L, 7127L, 7121L, 7111L,
7123L, 7147L, 7119L, 7106L, 7103L, 7091L, 7097L, 7103L, 7086L,
7099L, 7094L, 7139L, 7186L, 7198L, 7248L, 7274L, 7319L, 7329L,
7384L, 7410L, 7479L), C = c(2307L, 2296L, 2297L, 2287L, 2273L,
2259L, 2246L, 2230L, 2215L, 2194L, 2175L, 2110L, 2098L, 2074L,
2070L, 2107L, 2117L, 2128L, 2106L, 1687L, 1674L, 1664L, 1638L,
1641L, 1672L, 1679L, 1677L, 1675L, 1681L, 1675L, 1665L, 1697L,
1694L, 1693L, 1693L, 1691L, 1703L, 1706L, 1700L, 1695L, 1698L,
1712L, 1688L, 1701L, 1693L, 1674L, 1690L, 1688L, 1710L, 1711L,
1692L, 1688L, 1700L, 1684L, 1755L, 1744L, 1764L, 1762L, 1753L,
1753L, 1768L, 1763L, 1788L)), class = "data.frame", row.names = c(NA,
-63L))
Following is how I calculate RMSE value when there is only ONE column. I am trying to have two betas at once instead of running the same codes multiple times.
beta<-seq(.05,.9,by=0.001)
RMSE<-NULL
for (i in seq_along(beta)){
fit<-holt(cretrain, beta=beta[i],h = length(cretest))
RMSE[i]<-accuracy(fit,cretest)[2,2]
}
beta.fit<-data_frame(beta,RMSE)
beta.min<-filter(beta.fit,RMSE==min(RMSE))
I am trying to get the best beta.min for each column and use it in Holt forecasting. Any suggestion is appreciated!