PARCIAL 5 5 June 2020, answers PDF

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ISTANBUL UNIVERSITY SCHOOL OF BUSINESS FORECASTING TECHNIQUES DOÇ. DR. NİHAT TAŞ SPRING- 2020 MID-TERM EXAM

Emre BABUR 1002150060

FORECASTING TECHNIQUES

QUESTION 1

autoplot(dole)

autoplot(bricksq)

autoplot(lynx)

autoplot(goog)

QUESTION 2

autoplot(arrivals)



The biggest number of arrivals came from New Zeland.

ggseasonplot(arrivals[,"Japan"])

ggseasonplot(arrivals[,"NZ"])

ggseasonplot(arrivals[,"UK"])

ggseasonplot(arrivals[,"US"])

QUESTION 3

gglagplot(hsales)

ggAcf(hsales,lag.max = 400)

gglagplot(usdeaths)

ggAcf(usdeaths,lag.max = 400)

gglagplot(bricksq)

ggAcf(bricksq,lag.max = 400)

gglagplot(sunspotarea)

ggAcf(sunspotarea,lag.max = 400)

gglagplot(gasoline)

ggAcf(gasoline,lag.max = 400)



seasonality: pattern exists when a series is influenced by seasonal factors (e.g., the quarter of the year, the month, or day of the week)



Trend: pattern exists when there is a long-term increase or decrease in the data.



Cyclic: pattern exists when data exhibit rises and falls that are not of fixed period (duration usually of at least 2 years).

QUESTION 4 ggAcf(cowtemp)



As you can see when we did daily temperature of cow’s ggAcf it seems like “B” picture

ggAcf(usdeaths)



As you can see when we did monthly accidental deaths’s ggAcf it seems like “A” picture

ggAcf(airpass)



As you can see when we did monthly air passengers’s ggAcf it seems like “D” picture

ggAcf(mink)



As you can see when we did annual milk trappings’s ggAcf it seems like “C” picture

QUESTION 5 dgoog...