piroyoung

#標本平均,普遍分散のヒストグラム
setwd("~/Desktop")
Num.repeat <- 1.0 * 10^5
List.flex <- c(2,3,4,5,6,7)
Tran <- "40"
List.color<- c("#0000ff","#3300cc","#660099","#990066","#cc0033","#ff0000")
Breaks <- 1000

piroyoung

Sample <- c(4,3,4,7,7,
			6,3,7,8,0,
			1,7,8,6,7,
			4,4,7,3,4)
n <- 8
Step <- 0.001
mcmcStep <- 20000
mcmcTimes <- 20
 
Z <- 1:mcmcStep

piroyoung

library(shiny)

# Define server logic required to generate and plot a random distribution
shinyServer(function(input, output) {
  

  output$distPlot <- renderPlot({
    
    N.sample <- input$obs
    N.mean <- 5000

piroyoung

library(shiny)

# Define UI for application that plots random distributions 
shinyUI(pageWithSidebar(
  
  # Application title
  headerPanel("Histgram of sample mean about dicerolling"),
  
  # Sidebar with a slider input for number of observations
  sidebarPanel(

piroyoung

data {
  int<lower=0> N;
  real x[N];
  real f[N];
  int<lower=0,upper=100> y[N];
}
parameters {
  real b0;
  real b1;
  real b2;

piroyoung

library(rstan)
library(coda)
setwd("~/R/stan_pois")

dat <- read.csv("data3a.csv",header = TRUE)
dat$f <- as.numeric(dat$f) -1  #カテゴリカルを01に変換

listed.dat <- list(x = dat$x , y = dat$y, f = dat$f, N=100)
fit<-stan(file="model.stan",data=conflict.dat,iter=5000,chains=3)
traceplot(fit)

piroyoung

# encoding: UTF-8
require "fileutils"
###random sampling

class ProcessCSV
	def initialize (orig)
		#本当はコンストラクタで禁則文字，文字コードの設定もしたい．
		@origFileName = orig
	end

piroyoung

#!/usr/bin/ruby
#! ruby -EUTF-8
# -*- mode:ruby; coding:utf-8 -*-
require 'MeCab'
require 'open-uri'
require 'nokogiri'

# スクレイピングするURL
url = []
selector = []

piroyoung

#encoding : utf-8

require 'twitter'
require 'pp'

client = Twitter::Streaming::Client.new do |config|
  config.consumer_key = '0CmP0LrH7vkuRweDR0ySKg'
  config.consumer_secret = 'fEeMhJQSZVMsVRQcYkx8SLgQmZ5a6V14Thm4IU3l8A'
  config.access_token = '147866733-qq35ey3FpaYWEUOdXjoyoj1iA9BlmiHDKNwzMX9Y'
  config.access_token_secret = '93R4bQAPvND9A0ZPfbcHIVHLc0AUZcvrmHZR7Al376NEb'

piroyoung

library(ggplot2)
library(reshape2)
setwd("~/work/R/ggplot2")

T <- 300
N <- 8

bm <- rnorm(T*N)
bm <- matrix(bm,nrow = T, ncol= N)
bm <- apply(bm, 2, cumsum)