# Resp <- data.frame(Response=rbinom(50,1,0.2), yhat=runif(50))
# Resp <- Resp[order(Resp$yhat,decreasing=TRUE),]

# ResponseX10    <- do.call(rbind, replicate(10, Resp, simplify=FALSE))
# str(ResponseX10)

# ResponseX10    <- ResponseX10[order(ResponseX10$yhat,decreasing=TRUE),]

# str(ResponseX10)
# head(ResponseX10)

# ResponseX10[[2]] <- NULL
# ResponseX10 <- data.frame(ResponseX10)
# str(ResponseX10)

# Draw 50 random numbers and replicate 10 times
Response <- rbinom(50, 1, 0.2)[rep(1:50, 10)]
yhat <- runif(50)[rep(1:50, 10)]
# Sort Response by yhat
Response <- Response[order(yhat, decreasing=TRUE)]

cum_R    <- cumsum(Response)
cum_R

# sam_size <- nrow(ResponseX10)
sam_size <- length(Response)
sam_size

# cum_n    <- seq(1:1,sam_size)
cum_n    <- seq(1, sam_size)
cum_n
# wt       <- rep(c(1), times=sam_size)
wt      <- rep(1, times=sam_size)
cum_wt   <- cumsum(wt)
cum_wt

dec      <- (cum_n/sam_size)
decc     <- floor((cum_n*10)/(sam_size+1))
str(decc)

# dec_mean <- aggregate(Response, by=list(decc), mean)

# dd_        <- data.frame(cum_R, sam_size, cum_wt, cum_n, decc)
# dd  <- cbind(Response, dd_)
# names(dd)[2] <- "cum_R"

dd        <- data.frame(Response, cum_R, sam_size, cum_wt, cum_n, decc)
dec_mean    <- aggregate(Response ~ decc, dd, mean)
dec_mean