R/m.infos.nest.aovlist.R

In ScottKnott: The ScottKnott Clustering Algorithm

m.infos.nest.aovlist <- function(x,
                                 my,
                                 forminter,
                                 which,
                                 fl1,
                                 fl2,
                                 sig.level,
                                 aux_mt,
                                 MSE,
                                 ...)
{

  aux_m.inf <- aggregate(forminter,
                         data = model.frame(x),
                         function(x) c(min = min(x),
                                       max = max(x),
                                       sd  = sd(x),
                                       se  = sd(x)/length(x),
                                       sepool  = sqrt(MSE/length(x))))

  aux_m.inf1 <- data.frame(aux_m.inf[names(aux_m.inf)!=my],
                           means     = aux_mt[[my]][,1],
                           aux_m.inf[[my]][,1:2],
                           'linf_sd' = aux_mt[[my]][,1] - aux_m.inf[[my]][,3],
                           'lsup_sd' = aux_mt[[my]][,1] + aux_m.inf[[my]][,3],
                           'linf_se' = aux_mt[[my]][,1] - abs(qt(sig.level,aux_mt[[my]][,2]))*aux_m.inf[[my]][,4],
                           'lsup_se' = aux_mt[[my]][,1] + abs(qt(sig.level,aux_mt[[my]][,2]))*aux_m.inf[[my]][,4],
                           'linf_sepool' = aux_mt[[my]][,1] - abs(qt(sig.level,aux_mt[[my]][,2]))*aux_m.inf[[my]][,5],
                           'lsup_sepool' = aux_mt[[my]][,1] + abs(qt(sig.level,aux_mt[[my]][,2]))*aux_m.inf[[my]][,5])

  aux_m.inf2 <- aux_m.inf1[order(aux_m.inf1[['means']],
                                 decreasing = TRUE),] 

  nf1 <- unlist(strsplit(which,
                         split = ':'))[1] # nome do primeiro fator do which

  nf2 <- unlist(strsplit(which,
                         split = ':'))[2] # nome do segundo fator do which

  nf3 <- unlist(strsplit(which,
                         split = ':'))[3] # nome do terceiro fator do which 

  if(is.null(fl2)){


    f2 <- levels(model.frame(x)[,nf1])[fl1] # corresponde ao fator onde se esta fazendo o desdobramento!

    aux_m.inf21 <- subset(aux_m.inf2, 
                          eval(parse(text = nf1)) == f2) # pegando as medias de interesse

    m.inf <- list(Means = aux_m.inf21[,c(1:3)],
                  mm = aux_m.inf21[,c(1:2,4:5)],
                  sd = aux_m.inf21[,c(1:2,6:7)],
                  ic = aux_m.inf21[,c(1:2,8:9)],
                  icpool = aux_m.inf21[,c(1:2,10:11)]) 

  } else {

    f2 <- levels(model.frame(x)[,nf2])[fl2] 

    f3 <- levels(model.frame(x)[,nf1])[fl1]

    aux_m.inf21 <- subset(aux_m.inf2, 
                          eval(parse(text = nf1)) == f3 & eval(parse(text = nf2)) == f2) # pegando as medias de interesse

    m.inf <- list(Means = aux_m.inf21[,c(1:4)],
                  mm = aux_m.inf21[,c(1:3,5:6)],
                  sd = aux_m.inf21[,c(1:3,7:8)],
                  ic = aux_m.inf21[,c(1:3,9:10)],
                  icpool = aux_m.inf21[,c(1:3,11:12)])  
  }
}