Time Series Forecasting/Johnson \& Johnson a. Briefly describe the main concept used in Exponential Smoothing models. b. List three types of Exponential Smoothing models. Please draw a simple graph for each type, depicting what the forecasts would look like. c. Briefly define a Moving Average process (use notation/equations if needed). d. Briefly define an Autoregressive process (use notation/equations if needed). e. We want to fit an ARIMA model to the historical data that is available for Johnson \& Johnson stock. We estimate an ARIMA(0,1,2). Please write out the full equation for this model, using the coefficients from RStudio below. > auto. arima(johnson) series: johnson ARIMA(0,1,2) with drift Coefficients: ma1 ma2 drift 0.13680.21340.3901 s.e. 0.04690.04930.1039 sigma^2 =11.46: log likelihood =1178 AIC =2363.99 AIC =2364.08 BIC =2380.4 Enreracte from DIM In ol