# Types of Kriging: Ordinary, Simple, Universal, Indicator, Probability, and Disjunctive (Especially for GATE-Geospatial 2022)

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## Ordinary Kriging

Ordinary kriging assumes the model:

Where, is an unknown constant.

One of the main issues concerning ordinary kriging is whether the assumption of a constant mean is reasonable. Sometimes there are good scientific reasons to reject this assumption.

Ordinary kriging can use either semivariograms or covariances, use transformations and remove trends, and allow for measurement error.

## Simple Kriging

Simple kriging assumes the model:

Where, is a known constant.

Simple kriging can use either semivariograms or covariances, use transformations, and allow for measurement error.

## Universal Kriging

Universal kriging assumes the model:

Where is some deterministic function.

Universal kriging can use either semivariograms or covariances, use transformations, and allow for measurement error.

## Indicator Kriging

Indicator kriging assumes the model:

Where, is an unknown constant and is a binary variable. The creation of binary data may be using a threshold for continuous data, or it may be that the observed data is 0 or 1.

## Probability Kriging

Probability kriging assumes the model:

Where, and are unknown constants and is a binary variable created by using a threshold indicator, .

## Disjunctive Kriging

Disjunctive kriging assumes the model:

Where, is an unknown constant and is an arbitrary function of . Notice that you can write , so indicator kriging is a special case of disjunctive kriging.

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