Tutuchan

```{r diamonds_{{color}}_{{cut}}_plot}
diamonds %>% 
  filter(
    color == "{{color}}",
    cut   == "{{cut}}"
    ) %>% 
  ggplot(aes(carat, price, colour = clarity)) + 
  geom_point(show.legend = FALSE) + 
  labs(
    title = 'Price by carat for diamonds with color {{color}} and cut {{cut}}'

aagarw30

Title: reactiveValues() function
Description: With reactiveValues(), you can create your own reactive values. reactiveValues() Creates a list of objects that can be manipulated within a reactive context (within observer or observerEvent with dependency on changes in certain input or state of an object). reactiveValues() objects are not reactive themselves and do not re-execute themselves when input value changes unlike reactive objects. Powered by R, Shiny, and RStudio.
License: GPL-3
Author: Abhinav Agrawal
DisplayMode: Showcase
Tags: R, R Shiny,reactiveValues(), observeEvent()
Type: Shiny

tonyerskine

Instructions

1. Copy both files into the directory containing the files you want converted
2. Run excel-to-csv.bat

Note: This script requires Excel to be installed.

tbadams45

library(shiny)
library(dplyr)
library(ggplot2)


innerModUI <- function(id) {
  ns <- NS(id)
  
  fluidPage(fluidRow(
    uiOutput(ns("inner_slider")),

pvictor

# BB-8 --------------------------------------------------------------------

# Inspired by Brian Hough in http://codepen.io/bhough/pen/wawrPL



# Packages ----------------------------------------------------------------

library("dplyr")
library("ggplot2")

Pakillo

---
title: "Untitled"
author: "Francisco Rodriguez-Sanchez"
date: "Thursday, January 22, 2015"
output: html_document
---

<style type="text/css">

body, td {

gaberoo

##############################################################################
# Metropolis-Hastings MCMC
#
# Runs a Metropolis-Hasting MCMC chain for a given likelihood function.
# Proposal steps are sampled from a Gaussian distribution, either in a single
# step or sequentially over the parameter space.
#
# Input:
#   theta      : starting value of the chain
#   lik.fun    : likelihood function