# I know that the isapprox() function exists but IMO, it's a mess as it doesn't cover
# the real possibility of one of the two inputs being zero while its tolerance parameters
# don't have any real value in data science. This function here is designed to be used
# for checking if two variances are equal, before applying a t-test on the corresponding variables.
#
# Compatible with Julia 1.6

"""
    Usage: MoreOrLessEqual(x, y, [ret])

    where x, y = (non-negative) numbers to be compared
          ret = relative error threshold; optional, defaulting to 10% or 0.1

"""
function MoreOrLessEqual(x::Real, y::Real, ret::Float64 = 0.1)
    if x < eps() || y < eps(); return false; end
    m, M = ifelse(x < y, (x, y), (y, x))
    return M <= m*(1.0 + ret)
end