day2day: Functions for Day-to-Day Data Analysis

#
# corr_gen <- function(x, y) {
#   cl <- c(class(x), class(y))
#   if (cl[1] == "factor") {
#     if (cl[2] == "factor") {
#       k1 <- length(table(x)) - 1
#       r1 <- length(table(y)) - 1
#       n <- sum(table(x, y))
#       # denom <- min(length(table(x)), length(table(y))) - 1
#       # return(sqrt(chisq.test(x, y)$statistic / length(x) / denom))
#       # denom <- min(sum(!is.na(x)), sum(!is.na(y))) - 1
#       # cramers v with biased correction
#       adj <- max(0, chisq.test(x, y)$statistic / n - k1 * r1 / (n - 1))
#       return(sqrt(adj / min(k1, r1)))
#       # return(chisq.test(x, y)$p.value)
#     } else {
#       mo <- summary(lm( y ~ x))
#       return(sqrt(max(0, mo$adj.r.squared)))
#       # return(pf(mo$fstatistic[1], mo$fstatistic[2], mo$fstatistic[3],
#                 # lower.tail = FALSE))
#     }
#   } else if (cl[2] != "factor") {
#     mo <- gam(y ~ s(x))
#     # mo <- gam(y ~ s(x, bs="ts", k = 3))
#     return(sqrt(max(0, summary(mo)$r.sq)))
#     # return(summary(mo)$s.table[, 4])
#   } else {
#     mo <- summary(lm( x ~ y))
#     return(sqrt(max(0, mo$adj.r.squared)))
#     # return(pf(mo$fstatistic[1], mo$fstatistic[2], mo$fstatistic[3],
#     #           lower.tail = FALSE))
#   }
# }
# #' @title title.
# #'
# #' @description
# #' \code{function} description.
# #'
# #' @details
# #' details.
# #'
# #' @param par.
# #'
# #' @return return.
# #'
# #' @author Erick Albacharro Chacon-Montalvan
# #'
# #' @export
# corr <- function(data) {
#   metadata <- expand.grid(x = 1:ncol(data), y = 1:ncol(data))
#   metadata$corr <- NA
#   index <- metadata$y > metadata$x
#   metadata$corr[index] <- apply(subset(metadata, index), 1,
#                          function(x) corr_gen(data[, x[1]], data[, x[2]]))
#   corr <- matrix(metadata$corr, ncol(data), ncol(data))
#   corr[is.na(corr)] <- t(corr)[is.na(corr)]
#   diag(corr) <- 1
#   rownames(corr) <- colnames(corr) <- names(data)
#   return(corr)
# }