| a = Float64[] | |
| N = 1_000_000 | |
| for i in 1:N | |
| push!(a, 0.1) | |
| end | |
| push!(a, 10.0e8) |
| function timer(N::Integer) | |
| A = ones(N, N) | |
| B = ones(N, N) | |
| c = ones(N) | |
| @printf "%f\n" @elapsed (A * B) * c | |
| @printf "%f\n" @elapsed A * (B * c) | |
| return | |
| end |
| pq = PriorityQueue{Vector{Float64},Float64}() | |
| enqueue!(pq, [0.0, 110.0], 100.0) | |
| enqueue!(pq, [0.0, 0.0], 10.0) | |
| enqueue!(pq, [0.0, 10.0], 0.0) | |
| enqueue!(pq, [10.0, 10.0], 10.0) | |
| peek(pq) | |
| dequeue!(pq) |
This outlines a roadmap for basic statistical functionality that Julia needs to offer. It is heavily drawn from the table of contents for MASS.
| M <- matrix(c(1, 0, 0, 1), byrow = 1, nrow = 2) | |
| df <- data.frame(A = 1) | |
| df$B <- list(M) | |
| df | |
| # A B | |
| # 1 1, 0, 0, 1 |
| # Code that takes a function, | |
| # a vector, | |
| # x0::Vector{Float64} - Initial point | |
| # x1::Vector{Float64} - Resulting point | |
| # gr::Vector{Float64} - Gradient | |
| # i::Integer - Index of current parameter being updated | |
| # f::Function - Log pdf of x | |
| # Ported from Radford Neal's R code, with a few thinggs missing |
| function maxdiff(x::Vector, y::Vector) | |
| n = length(x) | |
| if length(y) != n | |
| throw(ArgumentError("Length of x and y must match")) | |
| end | |
| d = 0.0 | |
| for i in 1:n | |
| d = max(d, abs(x[i] - y[i])) | |
| end | |
| return d |
| function isidentifier(s::String) | |
| n = length(s) | |
| if n == 0 | |
| return false | |
| end | |
| i = 0 | |
| for c in s | |
| i += 1 | |
| if i == 1 | |
| if !(isalpha(c) || c == '_') |
Let D be any distribution over the integers. Suppose that the first moment exists for D and is an irrational number.
In this case, the sample mean is never exactly equal to the true mean because the sample mean is always a rational number.
This is simple to prove: the sample mean is always a sum of integers divided by the number of samples, which is always an integer.
| foo <- function(frame_number) | |
| { | |
| assign("frame_number", -1, envir = sys.frame(frame_number)) | |
| } | |
| bar <- function() | |
| { | |
| frame_number <- sys.nframe() | |
| print(frame_number) | |
| foo(frame_number) |