These are the R codes to implement the algorithms and figures in Costa, Lopes & Singer (2015).
The MIT License (MIT)
These are the R codes to implement the algorithms and figures in Costa, Lopes & Singer (2016).
The MIT License (MIT)
| # benford_file.R | |
| # | |
| # Copyright (c) 2017 Eliardo Costa | |
| # | |
| # This program is free software; you can redistribute it and/or modify | |
| # it under the terms of the BSD Zero Clause License as published by | |
| # Rob Landley. See http://spdx.org/licenses/0BSD.html for more details. | |
| benford_file <- function(vecdata, filename, source.url, ds) { | |
| cd <- getwd() |
1- Go to Tools -> Global Options -> Code -> Snippets -> Edit Snippets.
2- Then paste the following code:
snippet mit
`r paste('# script.R')`
`r paste('#')`
`r paste('# The MIT License (MIT)')`
`r paste('#')`
`r paste('# Copyright (c)', format(Sys.time(), "%Y"), '<Your name>')`
`r paste('#')`
1- Go to Tools -> Global Options -> Code -> Snippets -> Edit Snippets.
2- Then paste the following code:
snippet 0bsd
`r paste('# script.R')`
`r paste('#')`
`r paste('# Copyright (c)', format(Sys.time(), "%Y"), '<Your name>')`
`r paste('#')`
`r paste('# This program is free software; you can redistribute it and/or modify')`
`r paste('# it under the terms of the BSD Zero Clause License as published by')`
| {fileheader} | |
| main <- function() { | |
| return(cat()) | |
| } | |
| if(interactive()) main() |
| r <- 0.5 # raio da circunferencia | |
| n <- 1E5 | |
| x <- runif(n) | |
| y <- runif(n) | |
| pdentro <- numeric(n) | |
| for (i in seq_len(n)) { # contando os pontos dentro da circunferencia | |
| pdentro[i] <- ifelse((x[i] - 0.5)^2 + (y[i] - 0.5)^2 <= r^2, 1, 0) | |
| } |
| n <- 50 | |
| w <- 1 | |
| set.seed(161017) | |
| lam <- sample(c(5, 25, 50), n, replace = TRUE, prob = c(0.35, 0.3, 0.35)) # 3 clusters! | |
| x <- rpois(n, w*lam) | |
| hist(x, prob = TRUE, breaks = 15) | |
| source("https://gist.githubusercontent.com/eliardocosta/7c350eece9f09a7caa0f48852621063c/raw/dd6eae6d9bb3101bdeeff0d9d087db91f9d7e74d/ppostPoiDP.R") | |
| foo <- ppostPoiDP(x = x, w = w, phi = sqrt(mean(x)/var(x)), lam0 = mean(x), alpha = 1, nburn = 500, nsam = 1E3) | |
| hist(foo$nclu) # histograma num. de clusters por iteracao | |
| plot(foo$lam, foo$fdist) # distribuicao acumulada a posteriori |
These are the R codes to implement the illustrative example in Costa, Paulino & Singer (2020, submitted).
The MIT License (MIT)
Copyright (c) 2020 Eliardo G. Costa, Carlos Daniel Paulino & Julio M. Singer
Permission is hereby granted, free of charge, to any person obtaining a copy of
| # Adaptacao da funcao 'mwar.ani' do pacote 'animation' do R para | |
| # ilustrar o conceito de media movel para k observacoes consecutivas | |
| mm.ani = function(x, k = 7, mat = matrix(1:2, 2), | |
| widths = rep(1, ncol(mat)), | |
| heights = rep(1, nrow(mat)), lty.rect = 2, ...) { | |
| nmax = ani.options('nmax') | |
| n = length(x) | |
| if (k > n) | |
| stop('A largura da janela k deve ser menor que o tamanho de x!') |