Homework 9 (submit by Dec 8, 11:59 pm EST on Classes as a single PDF file) 1. Load the data kings in R using kings

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Homework 9 (submit by Dec 8, 11:59 pm EST on Classes as a single PDF file) 1. Load the data kings in R using kings <- scan("http://robjhyndman.com/tsdldata/misc/kings.dat",skip="3)" the="" data="" contain="" the="" age="" of="" death="" of="" successive="" kings="" of="" england,="" starting="" with="" william="" the="" conqueror.="" a.="" store="" the="" data="" in="" a="" time="" series.="" b.="" plot="" the="" time="" series.="" 2.="" load="" the="" data="" births="" in="" r="" using="" births=""><- scan("http://robjhyndman.com/tsdldata/data/nybirths.dat")="" the="" data="" contain="" the="" number="" of="" births="" per="" month="" in="" new="" york="" city,="" from="" january="" 1946="" to="" december="" 1959.="" a.="" store="" the="" data="" in="" a="" time="" series.="" b.="" plot="" the="" time="" series="" and="" identify="" any="" component="" (i.e.,="" trend,="" seasonal,="" irregular)="" c.="" subset="" the="" time="" series="" from="" oct="" 1949="" to="" may="" 1955.="" d.="" decompose="" the="" time="" series="" and="" interpret="" the="" result.="" 3.="" load="" the="" data="" rain="" in="" r="" using="" rain=""><- scan("http://robjhyndman.com/tsdldata/hurst/precip1.dat",skip="1)" the="" data="" contain="" the="" total="" annual="" rainfall="" in="" inches="" for="" london,="" from="" 1813="" to="" 1912.="" a.="" store="" the="" data="" in="" a="" time="" series.="" b.="" plot="" the="" time="" series="" and="" identify="" any="" component.="" c.="" model="" the="" time="" series="" using="" a="" single="" exponential="" model="" and="" interpret="" the="" result.="" d.="" make="" a="" forecast="" of="" the="" total="" annual="" rainfall="" from="" 1913="" to="" 1918="" using="" your="" model="" in="" c.="" visualize="" your="" forecast.="" 4.="" load="" the="" data="" skirts="" in="" r="" using="" skirts=""><- scan("http://robjhyndman.com/tsdldata/roberts/skirts.dat",skip=5) the data contain the annual diameter of women's skirts at the hem, from 1866 to 1911. a. store the data in a time series. b. plot the time series. c. fit a model using automated forecasts and interpret the result. scan("http://robjhyndman.com/tsdldata/roberts/skirts.dat",skip="5)" the="" data="" contain="" the="" annual="" diameter="" of="" women's="" skirts="" at="" the="" hem,="" from="" 1866="" to="" 1911.="" a.="" store="" the="" data="" in="" a="" time="" series.="" b.="" plot="" the="" time="" series.="" c.="" fit="" a="" model="" using="" automated="" forecasts="" and="" interpret="" the="">