ar_1_simulation.Rmd

---
title: "Simulate Time Series"
runtime: shiny
output: html_document
---
This is an interactive document.  It interactively simmulates a Moving average order 1 model.
The same code that could simulate the series non interactively is also included.

Make sure you have the following packages installed on your system.
```{r,echo=FALSE,message=FALSE}
# load packages ####
# if you do not have these packages - install.packages('package name')
library(tidyquant)
library(quantmod)
library(dplyr)
library(tidyverse)
library(ggplot2)
library(lubridate)
library(xts)
library(shiny)
```

```{r,echo=FALSE}
inputPanel(
  sliderInput("phi","Correlation: ",min=0, max=.9999,value=0.5)
)
``` 
```{r,echo=FALSE}
x <- reactive({ 
  date <- seq.Date(as.Date("2001/01/01"),as.Date("2013/01/01"),"days") 
  l <- length(date) 
  y <-arima.sim(model=list(ar=c(input$phi)),n=l) 
  d <- data.frame(date=date,y=y) 
  x <- xts(d[,-1],order.by = d[,1]) 
})
```

all the results of the fit.  

```{r,echo=FALSE}
renderPlot({

plot(x())
 
})
``` 
```{r,echo=FALSE}
renderPlot({
pacf(x())
})
```


```{r,echo=FALSE,include=FALSE,eval=FALSE}
  date <- seq.Date(as.Date("2001/01/01"),as.Date("2013/01/01"),"days") 
  l <- length(date) 
  y <-arima.sim(model=list(ar=c(0.5)),n=l) 
  d <- data.frame(date=date,y=y) 
  x <- xts(d[,-1],order.by = d[,1]) 
```

```{r,echo=FALSE,include=FALSE,eval=FALSE}
plot(x)
``` 

```{r,echo=FALSE,include=FALSE,eval=FALSE}
pacf(x)
```