An example of the non-transitivity of the Wilcoxon test, using Efron's non-transitive dice.
refron() generates numbers from a set of four non-transitive dice, so that a beats b beats c beats d beats a two-thirds of the time, with optional Gaussian smoothing.
example.R does Wilcoxon rank-sum tests to show that a > b > c > d > a
| <!DOCTYPE html> | |
| <html lang="en" > | |
| <head> | |
| <meta charset="UTF-8"> | |
| <title>Epiphany Clock</title> | |
| <link rel='stylesheet prefetch' href='http://maxcdn.bootstrapcdn.com/bootstrap/3.3.5/css/bootstrap.min.css'> |
| library(tidyverse) | |
| library(leaflet) | |
| library(jsonlite) | |
| library(ratelimitr) | |
| library(htmlwidgets) | |
| library(htmltools) | |
| allroutes<-read_csv("~/Downloads/WLG-google-transit/routes.txt") %>% filter(route_type==3) | |
| download_route<-limit_rate( |
| # Based on https://gist.github.com/tjvananne/8b0e7df7dcad414e8e6d5bf3947439a9 | |
| # Rewritten to work chunk by chunk, so I can read the 42B file with only 8GB memory | |
| # input .txt file, exports list of list of values and character vector of names (words) | |
| proc_pretrained_vec <- function(filename, chunksize=1000, guess_size=100000) { | |
| size<-guess_size | |
| here<-0 | |
| # initialize space for values and the names of each word in vocab | |
| vals <- vector(mode = "list", length(size)) |
| library(shiny) | |
| # Define UI for application that draws a histogram | |
| ui <- fluidPage( | |
| # Application title | |
| titlePanel("Bayesian Surprise"), | |
| # Sidebar with a slider input for number of bins |
| withPV<-function(mapping, design, action, ...) UseMethod("withPV",design) | |
| withPV.survey.design<-function(mapping, design, action,...){ | |
| if(inherits(mapping,"formula")) mapping<-list(mapping) | |
| if (!is.list(mapping)) | |
| stop("'mapping' must be a list of formulas") | |
| if (!all(sapply(mapping, length)==3)) |
| ## from: https://www.stats.govt.nz/information-releases/property-transfer-statistics-march-2019-quarter | |
| re<-read.table(text= | |
| "year quarter citbuy citsell resbuy ressell fornbuy fornsell corpbuy corpsell knowbuy knowsell unkbuy unksell total | |
| 2017 Mar 23592 23490 2130 1101 621 375 3060 4407 29406 29370 4287 4320 33690 | |
| 2017 Jun 30414 30678 3063 1512 930 486 4188 5946 38595 38625 450 426 39048 | |
| 2017 Sep 27123 27021 2703 1458 783 441 3618 5316 34230 34239 126 117 34356 | |
| 2017 Dec 28632 28125 2862 1491 1038 468 3663 6111 36195 36192 84 87 36279 | |
| 2018 Mar 25881 25947 2625 1401 1083 501 3255 4998 32841 32847 39 36 32880 | |
| 2018 Jun 31044 31173 3171 1656 1116 492 4281 6285 39606 39606 21 21 39627 | |
| 2018 Sep 28284 27684 2982 1557 717 378 3630 5997 35613 35613 21 21 35634 |
| ## startup | |
| library(jsonlite) | |
| library(httr) | |
| library(knitr) | |
| library(kableExtra) | |
| options(stringsAsFactors=FALSE) | |
| ## These two files are part of the static GTFS information | |
| routes<-read.csv("./routes.txt") | |
| routes$route_id<-substr(as.character(routes$route_id),1,5) ## remove versioning info |
| ## https://doi.org/10.1093/jssam/smz010 | |
| make.s<-function(mu, sigma,tau2,alpha){ | |
| g<-make.g(alpha) | |
| invg<-make.ginv(alpha) | |
| function(theta) invg(2*sigma*(theta-mu)/tau2) | |
| } | |
| make.g<-function(alpha){ |
| library(AER) | |
| svyivreg<-function(formula, design, ...) UseMethod("svyivreg",design) | |
| svyivreg.survey.design<-function(formula, design){ | |
| .data<-model.frame(design) | |
| .data$.weights<-weights(design,"sampling") | |
| model<- ivreg(formula, data=.data, weights=.weights) |