Discussion 2

Load Libraries / Load Data

library(tidyverse)

## -- Attaching packages ------------------------------------------ tidyverse 1.2.1 --

## v ggplot2 3.2.1     v purrr   0.3.2
## v tibble  2.1.3     v dplyr   0.8.3
## v tidyr   0.8.3     v stringr 1.4.0
## v readr   1.3.1     v forcats 0.4.0

## -- Conflicts --------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(mosaic)

## Loading required package: lattice

## Loading required package: ggformula

## Loading required package: ggstance

## 
## Attaching package: 'ggstance'

## The following objects are masked from 'package:ggplot2':
## 
##     geom_errorbarh, GeomErrorbarh

## 
## New to ggformula?  Try the tutorials: 
##  learnr::run_tutorial("introduction", package = "ggformula")
##  learnr::run_tutorial("refining", package = "ggformula")

## Loading required package: mosaicData

## Loading required package: Matrix

## 
## Attaching package: 'Matrix'

## The following object is masked from 'package:tidyr':
## 
##     expand

## Registered S3 method overwritten by 'mosaic':
##   method                           from   
##   fortify.SpatialPolygonsDataFrame ggplot2

## 
## The 'mosaic' package masks several functions from core packages in order to add 
## additional features.  The original behavior of these functions should not be affected by this.
## 
## Note: If you use the Matrix package, be sure to load it BEFORE loading mosaic.

## 
## Attaching package: 'mosaic'

## The following object is masked from 'package:Matrix':
## 
##     mean

## The following objects are masked from 'package:dplyr':
## 
##     count, do, tally

## The following object is masked from 'package:purrr':
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##     cross

## The following object is masked from 'package:ggplot2':
## 
##     stat

## The following objects are masked from 'package:stats':
## 
##     binom.test, cor, cor.test, cov, fivenum, IQR, median,
##     prop.test, quantile, sd, t.test, var

## The following objects are masked from 'package:base':
## 
##     max, mean, min, prod, range, sample, sum

library(ggformula)
library(readr)
library(fpp2)

## Loading required package: forecast

## Registered S3 method overwritten by 'xts':
##   method     from
##   as.zoo.xts zoo

## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo

## Registered S3 methods overwritten by 'forecast':
##   method             from    
##   fitted.fracdiff    fracdiff
##   residuals.fracdiff fracdiff

## Loading required package: fma

## Loading required package: expsmooth

BMY <- read_csv("E:/WOODS/ADECXXXX/BMY.csv")

## Parsed with column specification:
## cols(
##   Date = col_character(),
##   Open = col_double(),
##   High = col_double(),
##   Low = col_double(),
##   Close = col_double(),
##   AdjClose = col_double(),
##   Volume = col_double()
## )

#Explore the data a bit

bmyts <- ts(BMY$AdjClose, frequency = 7, start = c(11, 4))
summary(bmyts)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   42.41   50.27   53.74   54.37   58.53   69.88

plot.ts(bmyts, xlab = "day", ylab = "Adjusted Daily Close", main = "Bristol Myers Squib, 11/4/14 thru 10/25/19")

#Decompose Additive

bmyaddcomp <- decompose(bmyts)
plot(bmyaddcomp)

#Decompose Multiplicative

bmymulcomp <- decompose(bmyts, type=c("multiplicative"))
plot(bmymulcomp)