Use the dataset from the fma library in R called “motel”. The…

Question Answered step-by-step Use the dataset from the fma library in R called “motel”. The… Use the dataset from the fma library in R called “motel”. The dataset contains information about motel occupancies in Australia. 1.  Convert the dataset into a tsibble (use this throughout the midterm). Please explain the Roomnights and Takings variables in this dataset in words that anyone can understand.  2.  What is the frequency of the dataset? 3.  Use the STL function on the Roomnights variable. What can you say about the trend, seasonality and remainder? Report the values for FT and FS (see section 4.3 in the text). Does the data need to be transformed in some way? If so do everything else with the transformed data. 4.  Calculate forecasts for the last 10 months (make a training dataset etc.) of the Roomnights variable using seasonal naïve, naïve, random walk with drift and STL forecasts. 5.  Calculate forecasts for the last 10 months using a linear model that includes a trend variable and other variables that account for seasonality and/or any other variable that helps explain Roomnights. 6.  Make a plot of the data on the original scale.  Add the five forecasts (with the prediction intervals for the linear model forecasts). Which model produces the biggest prediction intervals on the original scale? 7.  Calculate accuracy measures RMSE, MAE, MAPE and MASE for the four forecasts for the out of sample forecast. Which model is best based on forecast accuracy? Computer Science Engineering & Technology Object-Oriented Programming BUSN FIN 642 Share QuestionEmailCopy link Comments (0)