State

State for the Kalman Filter

time: the current timestep
mt: the posterior mean of the latent state
ct: the posterior covariance of the latent state
at: the prior mean of the latent state
rt: the prior covariance of the latent state
qt: the one step predicted observation covariance, not present at the first timestep

Linear Supertypes

Serializable, Serializable, Product, Equals, AnyRef, Any

Instance Constructors

new State(time: Double, mt: DenseVector[Double], ct: DenseMatrix[Double], at: DenseVector[Double], rt: DenseMatrix[Double], ft: Option[DenseVector[Double]], qt: Option[DenseMatrix[Double]])

time
the current timestep
mt
the posterior mean of the latent state
ct
the posterior covariance of the latent state
at
the prior mean of the latent state
rt
the prior covariance of the latent state
qt
the one step predicted observation covariance, not present at the first timestep

Value Members

final def !=(arg0: Any): Boolean

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

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

Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0

Definition Classes
Any
val at: DenseVector[Double]

the prior mean of the latent state
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
val ct: DenseMatrix[Double]

the posterior covariance of the latent state
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
val ft: Option[DenseVector[Double]]
final def getClass(): Class[_]

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

Definition Classes
Any
val mt: DenseVector[Double]

the posterior mean of the latent state
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val qt: Option[DenseMatrix[Double]]

the one step predicted observation covariance, not present at the first timestep
val rt: DenseMatrix[Double]

the prior covariance of the latent state
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
val time: Double

the current timestep
final def wait(): Unit

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

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

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Doc: package KalmanFilter

case class State(time: Double, mt: DenseVector[Double], ct: DenseMatrix[Double], at: DenseVector[Double], rt: DenseMatrix[Double], ft: Option[DenseVector[Double]], qt: Option[DenseMatrix[Double]]) extends Product with Serializable

Instance Constructors

new State(time: Double, mt: DenseVector[Double], ct: DenseMatrix[Double], at: DenseVector[Double], rt: DenseMatrix[Double], ft: Option[DenseVector[Double]], qt: Option[DenseMatrix[Double]])

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

val at: DenseVector[Double]

def clone(): AnyRef

val ct: DenseMatrix[Double]

final def eq(arg0: AnyRef): Boolean

def finalize(): Unit

val ft: Option[DenseVector[Double]]

final def getClass(): Class[_]

final def isInstanceOf[T0]: Boolean

val mt: DenseVector[Double]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val qt: Option[DenseMatrix[Double]]

val rt: DenseMatrix[Double]

final def synchronized[T0](arg0: ⇒ T0): T0

val time: Double

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped