Kriging predictor minimizes the variance of the prediction errorQuestion 5Answera.Yesb.No

The correct answer is: a. Yes.

Kriging is a statistical method used in geostatistics for interpolation and predicting unknown values at certain locations based on known values from nearby locations. One of the key features of the Kriging predictor is its focus on minimizing the variance of prediction errors.

In Kriging, predictions are made using the weighted averages of known values, and the weights are determined to achieve the best linear unbiased estimation. The method relies on the spatial correlation of data points, which allows Kriging to account for both the predicted values and their associated uncertainties. By minimizing the variance of prediction errors, Kriging provides not only predictions of unknown values but also an estimate of the uncertainty surrounding those predictions, which is crucial in various applications such as environmental science, mining, and resource management.

In conclusion, Kriging does indeed minimize the variance of the prediction error, confirming the answer as a. Yes.