object LSMR extends SerializableLogging
Nearly direct port of http://www.mathworks.com/matlabcentral/fileexchange/27183-lsmr--an-iterative-algorithm-for-least-squares-problems (BSD licensed code)
http://web.stanford.edu/group/SOL/software/lsmr/
The only difference is that they square the regularization factor.
- Alphabetic
- By Inheritance
- LSMR
- SerializableLogging
- Serializable
- AnyRef
- Any
- Hide All
- Show All
- Public
- Protected
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
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @IntrinsicCandidate()
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @IntrinsicCandidate()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @IntrinsicCandidate()
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def logger: LazyLogger
- Attributes
- protected
- Definition Classes
- SerializableLogging
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @IntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @IntrinsicCandidate()
- def solve[M, MT, V](A: M, b: V, regularization: Double = 0.0, tolerance: Double = 1E-9, maxIter: Int = 1000, quiet: Boolean = false)(implicit multMV: operators.OpMulMatrix.Impl2[M, V, V], transA: CanTranspose[M, MT], multMTV: operators.OpMulMatrix.Impl2[MT, V, V], ispace: MutableInnerProductVectorSpace[V, Double]): V
Solves the problem min pow(norm(A * x - b), 2) + regularization * pow(norm(x), 2)
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])