Start learning 50% faster. Sign in now
The ARIMA model is widely used for time series forecasting because it combines two key components: autoregressive (AR), which uses past data points to model future values, and moving average (MA), which smooths out short-term fluctuations in the data. Additionally, integration (I) is used to make a non-stationary time series stationary by differencing the data. This allows ARIMA to be applied to a wide range of time series data, even if they exhibit complex patterns, provided the data can be made stationary. Option A is incorrect because ARIMA requires the data to be stationary (or at least made stationary through differencing). Option B is incorrect because ARIMA can handle data with both long-term trends and periodic fluctuations. Option D is incorrect because ARIMA is not the best model for time series with seasonal components—SARIMA (Seasonal ARIMA) is more appropriate for that. Option E is incorrect because ARIMA can handle irregular components as long as the data is stationary or can be made stationary.
Recently, which of these states have exported its first consignment of plant based meat products to the USA?
Which state in India is known for its significant cement production industry.
The Archaeological Survey of India declared that entry to all ticketed Centrally protected historic monuments would be free of charge from _____ to ____...
L&T Technology Services, a provider of high-end engineering services, has disclosed that _____ luxury automaker had awarded it a five-year contract ...
From which Vedic text is the knowledge of rituals related to Yagya primarily derived?
The PM Gati Shakti Multimodal Waterways Summit will be held in which city of Uttar Pradesh?
Which state will be hosting the National Winter Games, 2023?
On what is the principle of Brahmo Samaj based?
What was the theme for the India Water Week that was celebrated from 1st to 5th November, 2022 at Greater Noida, India.
When was the Gandhi-Irwin Pact carried out?