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# GaussianWeight 

#### trait GaussianWeight extends SimpleBlockSampler with DoubleWeight

Assigns weights to continuous variables based on a Gaussian PDF with a static variance

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Inherited
1. GaussianWeight
2. DoubleWeight
3. SimpleBlockSampler
4. BlockSampler
5. AnyRef
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### Abstract Value Members

1. abstract val variance: Double

The static variance used to compute the compatibility function

### Concrete 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
Definition Classes
DoubleWeightBlockSampler
5. final def asInstanceOf[T0]: T0
Definition Classes
Any
6. val block
Definition Classes
BlockSampler
7. val blockInfo
Definition Classes
BlockSampler
8. def clone(): AnyRef
Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
9. def computeSamplingFactor(currentSamples: Map[Variable[_], Int]): Factor[Double]
Definition Classes
SimpleBlockSampler
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 getSamplingFactor(currentSamples: Map[Variable[_], Int]): Factor[Double]

Get the factor from which to sample this block Returns a non-logarithmic factor

Get the factor from which to sample this block Returns a non-logarithmic factor

Definition Classes
SimpleBlockSamplerBlockSampler
15. def hashCode(): Int
Definition Classes
AnyRef → Any
16. val indexMap: Map[Variable[_], Int]
Definition Classes
SimpleBlockSampler
17. val indices
Definition Classes
SimpleBlockSampler
18. final def isInstanceOf[T0]: Boolean
Definition Classes
Any
19. def logWeight(resultValue: Double, chainValue: Double): Double

Function with which to assign weights in place of -Infinity.

Function with which to assign weights in place of -Infinity. It is assumed that if chainValue == resultValue, the result is 0.0. Observe that setting this function to:

`if(chainValue == resultValue) 0.0 else Double.NegativeInfinity`

has the same effect as not using the DoubleWeight trait at all.

Definition Classes
GaussianWeightDoubleWeight
20. final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
21. def normalizeFactor(factor: Factor[Double]): Factor[Double]

Normalize a factor so its weights sum to 1 Takes a logarithmic factor and returns a non-logarithmic factor

Normalize a factor so its weights sum to 1 Takes a logarithmic factor and returns a non-logarithmic factor

Definition Classes
SimpleBlockSampler
22. final def notify(): Unit
Definition Classes
AnyRef
23. final def notifyAll(): Unit
Definition Classes
AnyRef
24. def sample(currentSamples: Map[Variable[_], Int]): Unit

Sample this block once

Sample this block once

Definition Classes
BlockSampler
25. def sampleFactor(factor: Factor[Double]): List[Int]

Select a set of indices in the factor according to the weights in the factor Works on a non-logarithmic factor

Select a set of indices in the factor according to the weights in the factor Works on a non-logarithmic factor

Definition Classes
BlockSampler
26. val semiring
Definition Classes
SimpleBlockSampler
27. final def synchronized[T0](arg0: ⇒ T0): T0
Definition Classes
AnyRef
28. def toString(): String
Definition Classes
AnyRef → Any
29. final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
30. final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )
31. final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws( ... )