R programming coding : library : fpp or fpp2

Provide plots for time series. Implement the autocorrelation analysis including correlogram of the residuals and the Ljung-Box test with lag 8. Answer the question if autocorrelation, and seasonality exists. Marking rules for a) to c): 0.25 for each step (0.25 for forecast plot, 0.25 for autocorrelation plot, 0.25 for portmanteaux test, and 0.25 for correct conlusion). (a) Annual bituminous coal production (19201968). Data set bicoal. Use nave. (b) Price of chicken (19241993). Data set chicken. Use seasonal nave. (c) Monthly total of people on unemployed benefits in Australia (January 1956July 1992). Data set dole. Use drift (d) Plot residuals for this forecast and compare them with the residuals of seasonal naive forecast. (e) Monthly total of accidental deaths in the United States (January 1973December 1978). Data set usdeaths. Use seasonal nave. (f) Quarterly production of bricks (in millions of units) at Portland, Australia (March 1956September 1994). Data set bricksq. Use mean method.

(g) What is the more appropriate method of forecast for this data? Implement it and justify your answer. (h) Annual Canadian lynx trappings (18211934). Data set lynx. Choose the optimal method. Implement for it the same autocorrelation analysis as above.