Statistics - Estimate the ETS Mode - R Studio Assessment Answer

ETS Mode R Studio Assessment Answer

Assignment Task: Q1.Plot your time series. By observing the plot and describing its components select an ETS model you think is appropriate for forecasting. Make sure you justify your choice (no more than 150 words). Q2. Estimate the ETS model you described in Question 1. Paste the estimated model output. Describe and comment on the estimated parameters and components. Include any plots you see necessary (no more than 150 words). Q3. Plot the residuals from the model and comment on these (no more than 50 words). Perform some diagnostic checks and comment on whether you are satisfied with the fit of the model. (Make sure you state all relevant information for any hypothesis test you perform such as the null hypothesis, the degrees of freedom, the decision, etc.). Q4Let R select an ets model. What model has been chosen and how has this model been chosen? (No more than 100 words). Q5.Comment on how the model chosen by R is different to the model you have specified (no more than 50 words). Which of the two models would you choose and why? (no more than 50 words). (Hint: think about model selection here but also check your residuals). If the models are identical specify a plausible alternative and compare it to the one from Questions 1, 2 and 3. Give a brief justification for your choice (no more than 100 words). (Hint: also check the residuals from this model). Q6. Generate forecasts for the period 2017-2018 using your chosen ETS model. Plot the forecasts and forecast intervals. Briefly comment on these. (No more than 100 words). Q7. On a different graph plot the last few years of your time series, forecasts and forecast intervals generated for the period 2017-2018 from both models you have considered in this assignment. Do both sets of forecasts look plausible? (No more than 100 words). (Hint: think about visualisation here, i.e., produce a graph that can help you compare the two sets of forecasts and forecast intervals). Q8. In the fourth and final individual assignment you will be expected to submit your code for all the assignments throughout the semester which should run without any errors. We will not be debugging code so if your code returns an error you will get zero marks for this part of the assignment. (Hint: refresh your R session so that everything is cleared from your Global Environment and rerun all your code to make sure that everything runs without errors). Use this question as preparation for that final submission and to get some feedback about good coding practices. We will only be briefly looking at your code and not running it in this instance. Here is a brief sample code you may find helpful # Code written by # for # Student number # packages included library() # set working directory setwd("...") # reading in my data y <- # Assignment 2 tasks # Q1 - get familiar with your data y %>% autoplot() y %>% ggseasonplot()

This R Studio Assessment has been solved by our R Studio experts at My Uni Paper. Our Assignment Writing Experts are efficient to provide a fresh solution to this question. We are serving more than 10000+ Students in Australia, UK & US by helping them to score HD in their academics. Our Experts are well trained to follow all marking rubrics & referencing style.