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ARIMA is a powerful forecasting method used for time series analysis, especially when the data is non-stationary. The AR (AutoRegressive) component accounts for the influence of past values on the current value, while the MA (Moving Average) component captures the dependency between an observation and a residual error. The “I” (Integrated) component makes the series stationary by differencing. This combination makes ARIMA flexible and suitable for various types of time series data, such as financial and economic data, where both autoregressive and moving average processes are relevant. Option A (Exponential Smoothing) is incorrect as it focuses on smoothing time series data, not on combining autoregressive and moving average features. Option B (Moving Average) is incorrect because it averages out short-term fluctuations but lacks an autoregressive component. Option C (Seasonal Decomposition) is incorrect as it decomposes a series without modeling dependencies. Option E (Linear Regression) is incorrect because it assumes a linear relationship and doesn’t account for time-lagged dependencies.
The issuance of sweat equity shares in the Company shall____________, of the paid -up equity capital of the Company at any time
The Court shall take Judicial Notice of certain facts. Which of the following facts is not included?
A mortgagor has right to inspect any document of title in the custody or power of mortgagee ________.
________________ in India is known as the court of record
Form of numerals to be used for the official purposes of the Union is?
A member or part time member of the Board shall not be appointed as Presiding Officer or Member of the Securities Appellate Tribunal
The delay in filing a complaint under Section 138 of Negotiable Instrument Act, 1881 can be condoned
Which of the following is an exception to the doctrine of privity of contract rule _______________?
Admission can be:_________.
The definition of fact is given in which section of the Act?