# OrdinaryKriging

### Related Docs: object OrdinaryKriging | package interpolation

#### class OrdinaryKriging extends Kriging

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Kriging, (Double, Double) ⇒ (Double, Double), AnyRef, Any
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### Instance Constructors

1. #### new OrdinaryKriging(points: Array[PointFeature[Double]], bandwidth: Double, sv: Semivariogram)

points

Sample points for Ordinary Kriging model training

bandwidth

The maximum inter-point pair-distances which influence the prediction

sv

The fitted Semivariogram to be used for prediction

### Value Members

1. #### final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
2. #### final def ##(): Int

Definition Classes
AnyRef → Any
3. #### final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
4. #### def absArray(arr: Array[Double]): Array[Double]

Returns the absolute values of a given array

Returns the absolute values of a given array

Attributes
protected
Definition Classes
Kriging
5. #### def apply(x: Double, y: Double): (Double, Double)

Definition Classes
Kriging → Function2
6. #### final def asInstanceOf[T0]: T0

Definition Classes
Any
7. #### def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
8. #### def createPredictorInit(numberOfPoints: Int): (Double, Double) ⇒ (Double, Double)

Ordinary Kriging training with the sample points

Ordinary Kriging training with the sample points

numberOfPoints

Number of points to be Kriged

Attributes
protected
Definition Classes
OrdinaryKrigingKriging
9. #### def curried: (Double) ⇒ (Double) ⇒ (Double, Double)

Definition Classes
Function2
Annotations
@unspecialized()
10. #### final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
11. #### def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
12. #### def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
13. #### final def getClass(): Class[_]

Definition Classes
AnyRef → Any
14. #### def getPointDistancesSorted(points: Array[PointFeature[Double]], minPoints: Int, bandwidth: Double, point: Point): Array[(Int, Double)]

Returns the indices of points close to the point for prediction within the given bandwidth

Returns the indices of points close to the point for prediction within the given bandwidth

Attributes
protected
Definition Classes
Kriging
Note

In case the number of points < minPoints; it returns the closest minPoints number of points

15. #### def hashCode(): Int

Definition Classes
AnyRef → Any
16. #### final def isInstanceOf[T0]: Boolean

Definition Classes
Any
17. #### final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
18. #### final def notify(): Unit

Definition Classes
AnyRef
19. #### final def notifyAll(): Unit

Definition Classes
AnyRef
20. #### def predict(pointMatrix: Array[Point]): Array[(Double, Double)]

Kriging Prediction for an Array of points

Kriging Prediction for an Array of points

pointMatrix

Points to be Kriged

returns

Tuples of (krigedValues, krigedVariance) for each of the kriged points

Definition Classes
Kriging
21. #### final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
22. #### def toString(): String

Definition Classes
Function2 → AnyRef → Any
23. #### def tupled: ((Double, Double)) ⇒ (Double, Double)

Definition Classes
Function2
Annotations
@unspecialized()
24. #### def varianceMatrixGen(sv: Semivariogram, points: Array[PointFeature[Double]]): RealMatrix

Attributes
protected
Definition Classes
Kriging
25. #### final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
26. #### final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
27. #### final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )