Module 12 assignment

 Module 12:

Code:

#Time Series for a Student Credit Card

#part a


#install.packages("timeSeries")

#install.packages("timeDate")


library(timeDate)

library(timeSeries)



require(timeSeries)



creditstudent <- c(31.9,27,31.3,31,39.4,40.7,42.3,49.5,45,50,50.9,58.5,39.4,36.2,40.5,44.6,46.8,44.7,52.2,54,48.8,55.8,58.7,63.4)


creditts <- ts(creditstudent, frequency=12, start=c(2012,1))


plot.ts(creditts)


#part b


creditpartb <- HoltWinters(x = creditts, beta = FALSE, gamma = FALSE)


creditpartb


#the observed and forecasted values re pretty close in similarity  but appears to lag. This is in the perspective of 

## the forecasted values against the actual observed values.


##More importantly the plot is shown without trend or seasonal component. This format of analysis decreases the weight of the vaue corresponded to time as time progresses onwards.



Console:

> #Time Series for a Student Credit Card

> #part a

> 

> #install.packages("timeSeries")

> #install.packages("timeDate")

> 

> library(timeDate)

> library(timeSeries)

> 

> 

> require(timeSeries)

> 

> 

> creditstudent <- c(31.9,27,31.3,31,39.4,40.7,42.3,49.5,45,50,50.9,58.5,39.4,36.2,40.5,44.6,46.8,44.7,52.2,54,48.8,55.8,58.7,63.4)

> 

> creditts <- ts(creditstudent, frequency=12, start=c(2012,1))

> 

> plot.ts(creditts)

> 

> #part b

> 

> creditpartb <- HoltWinters(x = creditts, beta = FALSE, gamma = FALSE)

> 

> creditpartb

Holt-Winters exponential smoothing without trend and without seasonal component.


Call:

HoltWinters(x = creditts, beta = FALSE, gamma = FALSE)


Smoothing parameters:

 alpha: 0.8232442

 beta : FALSE

 gamma: FALSE


Coefficients:

      [,1]

a 62.44453

> 

> #the observed and forecasted values re pretty close in similarity  but appears to lag. This is in the perspective of 

> ## the forecasted values against the actual observed values.

> 

> ##More importantly the plot is shown without trend or seasonal component. This format of analysis decreases the weight of the vaue corresponded to time as time progresses onwards.




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