Filling Missing Climate Data Using Arithmetic mean method, Inverse Distance Weighting method MCMC

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The arithmetic mean is the simplest and most widely used measure of a mean, or average. It simply involves taking the sum of a group of numbers, then dividing that sum by the count of the numbers used in the series.
Inverse distance weighting (IDW) is a type of deterministic method for multivariate interpolation with a known scattered set of points. The assigned values to unknown points are calculated with a weighted average of the values available at the known points.

Multiple Imputation is a Markov chain Monte Carlo technique developed to work out missing data problems.

Conclusion: The advantages of IDW are that it is simple, easy to understand, and efficient. Disadvantages are that it is sensitive to outliers and there is no indication of error.

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