Time series analysis ( statistical knowledge requires) question attached here. If model is not adequate, why? And model we can suggest/choice for better fit? Explain. If model is adequate, why? And mo

4. A seasonal ARIMA model was fitted to a monthly time series. A summary of the fitted model and some residual diagnostics are given below. Write down the mathematical equation of the fitted model in operator form. Is there evidence that the model is not adequate? If so, suggest a modification of the model that may lead to a better fit. Call: arima (x = y, order = c(2, 1, 1), seasonal = list (order = c(0, 1, 0), period = 12) Coefficients: ar1 ar2 mal 0. 8498 -0. 4475 0.5438 s. e. 0. 0508 0. 0482 0. 0466 sigma 2 estimated as 1.582: log likelihood = -803.8, aic = 1615.61 Standardized Residuals -3 -1 100 200 300 400 500 Time ACF of Residuals ACF 0.0 0.4 0.8 10 15 20 25 Lag p values for Ljung-Box statistic p value 0.0 0.4 0.8 o o O O O 10 15 20 lag