The time series forecasting method that gives equal weightage to each of the 'm' most recent observations is

Explanation:

Time Series Method:

In this method, past data are arranged in chronological order as dependent variable and time as independent variable. Some type of time series methods are as follows

Past Average Method:

• Forecast is given by the average or mean value of the actual demand data for the previous period.

Moving average Method: or rolling average Method:

• In this method, fresh average is calculated at the end of each period by adding the actual demand data for the most recent period and deleting the data for the order period. It gives equal weight to each of the most recent observations.

Weighted moving average Method:

• This method gives unequal weight to each demand data with more weight to recent data.

Exponential Smoothing Method:

• This method gives weight to all the previous data and the pattern of weight assigned is exponentially decreasing in order with most recent data is given the highest weight.

Kalman fitter:

• This is also an smoothing forecasting method which gives more weight to a particular trend.