## ---- echo = F, eval = TRUE, message = F, error = F---------------------- library(AHM) library(mixexp) if (0) { library(devtools); load_all() } ## ---- echo = TRUE, eval = T---------------------------------------------- data("coating") dat = coating h_tmp = 1.1 x = dat[,c("c1","c2","x11","x12","x21","x22")] y = dat[,ncol(dat)] ptm <- proc.time() out = ahm (y, x, num_major = 2, dist_minor = c(2,2), type = "weak", alpha=0, lambda_seq=seq(0,5,0.01), nfold = NULL, mapping_type = c("power"), powerh = h_tmp, rep_gcv=100) proc.time() - ptm summary(out) ## ---- echo = TRUE, eval = FALSE------------------------------------------ # powerh_path = round(seq(0.001,2,length.out =15),3) # # res = cv.ahm (y, x, powerh_path=powerh_path, metric = "mse", num_major=2, dist_minor=c(2,2), type = "weak", alpha=0, lambda_seq=seq(0,5,0.01), nfolds=NULL, mapping_type = c("power"), rep_gcv=100) # # object = res$metric_mse ## ---- echo = TRUE, eval = FALSE------------------------------------------ # data("pringles_fat") # data_fat = pringles_fat # h_tmp = 1.3 # # x = data_fat[,c("c1","c2","c3","x11","x12","x21","x22")] # y = data_fat[,1] # ptm <- proc.time() # out = ahm (y, x, num_major = 3, dist_minor = c(2,2,1), # type = "weak", alpha=0, lambda_seq=seq(0,5,0.01), nfold = NULL, # mapping_type = c("power"), powerh = h_tmp, # rep_gcv=100) # proc.time() - ptm ## ---- echo = TRUE, eval = FALSE------------------------------------------ # summary(out) # # coefficients = coef(out) # fitted = predict(out, x) # ## ---- echo = TRUE, eval = FALSE------------------------------------------ # data("pringles_hardness") # dat = pringles_hardness # h_tmp = 1.3 # # x = dat[,c("c1","c2","c3","x11","x12","x21","x22")] # y = dat[,1] # ptm <- proc.time() # out = ahm (y, x, num_major = 3, dist_minor = c(2,2,1), # type = "weak", alpha=0, lambda_seq=seq(0,5,0.01), nfold = NULL, # mapping_type = c("power"), powerh = h_tmp, # rep_gcv=100) # proc.time() - ptm # summary(out)