class
SliceSampler extends Iterator[Sample]
Instance Constructors
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new
SliceSampler(logLikelihoodFunc: LogLikelihood, init: DenseVector[Double], burnin: Int = 0, thin: Int = 0, componentwise: Boolean = true, initStep: Double = 1e-1, stepBase: Double = 2)
Type Members
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class
GroupedIterator[B >: A] extends AbstractIterator[Seq[B]] with Iterator[Seq[B]]
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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def
++[B >: Sample](that: ⇒ GenTraversableOnce[B]): Iterator[B]
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def
/:[B](z: B)(op: (B, Sample) ⇒ B): B
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def
:\[B](z: B)(op: (Sample, B) ⇒ B): B
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final
def
==(arg0: Any): Boolean
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def
addString(b: StringBuilder): StringBuilder
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def
addString(b: StringBuilder, sep: String): StringBuilder
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def
addString(b: StringBuilder, start: String, sep: String, end: String): StringBuilder
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def
aggregate[B](z: ⇒ B)(seqop: (B, Sample) ⇒ B, combop: (B, B) ⇒ B): B
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final
def
asInstanceOf[T0]: T0
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def
buffered: BufferedIterator[Sample]
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def
clone(): AnyRef
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def
collect[B](pf: PartialFunction[Sample, B]): Iterator[B]
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def
collectFirst[B](pf: PartialFunction[Sample, B]): Option[B]
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def
contains(elem: Any): Boolean
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def
copyToArray[B >: Sample](xs: Array[B], start: Int, len: Int): Unit
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def
copyToArray[B >: Sample](xs: Array[B]): Unit
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def
copyToArray[B >: Sample](xs: Array[B], start: Int): Unit
-
def
copyToBuffer[B >: Sample](dest: Buffer[B]): Unit
-
def
corresponds[B](that: GenTraversableOnce[B])(p: (Sample, B) ⇒ Boolean): Boolean
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def
count(p: (Sample) ⇒ Boolean): Int
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var
current: Sample
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val
dims: Int
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def
drop(n: Int): Iterator[Sample]
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def
dropWhile(p: (Sample) ⇒ Boolean): Iterator[Sample]
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def
duplicate: (Iterator[Sample], Iterator[Sample])
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final
def
eq(arg0: AnyRef): Boolean
-
def
equals(arg0: Any): Boolean
-
def
exists(p: (Sample) ⇒ Boolean): Boolean
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def
filter(p: (Sample) ⇒ Boolean): Iterator[Sample]
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def
filterNot(p: (Sample) ⇒ Boolean): Iterator[Sample]
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def
finalize(): Unit
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def
find(p: (Sample) ⇒ Boolean): Option[Sample]
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def
flatMap[B](f: (Sample) ⇒ GenTraversableOnce[B]): Iterator[B]
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def
fold[A1 >: Sample](z: A1)(op: (A1, A1) ⇒ A1): A1
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def
foldLeft[B](z: B)(op: (B, Sample) ⇒ B): B
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def
foldRight[B](z: B)(op: (Sample, B) ⇒ B): B
-
def
forall(p: (Sample) ⇒ Boolean): Boolean
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def
foreach[U](f: (Sample) ⇒ U): Unit
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final
def
getClass(): Class[_]
-
-
def
hasDefiniteSize: Boolean
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def
hasNext: Boolean
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def
hashCode(): Int
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def
indexOf[B >: Sample](elem: B): Int
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def
indexWhere(p: (Sample) ⇒ Boolean): Int
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def
isEmpty: Boolean
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final
def
isInstanceOf[T0]: Boolean
-
def
isTraversableAgain: Boolean
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def
length: Int
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def
map[B](f: (Sample) ⇒ B): Iterator[B]
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def
max[B >: Sample](implicit cmp: Ordering[B]): Sample
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def
maxBy[B](f: (Sample) ⇒ B)(implicit cmp: Ordering[B]): Sample
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def
min[B >: Sample](implicit cmp: Ordering[B]): Sample
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def
minBy[B](f: (Sample) ⇒ B)(implicit cmp: Ordering[B]): Sample
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def
mkString: String
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def
mkString(sep: String): String
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def
mkString(start: String, sep: String, end: String): String
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final
def
ne(arg0: AnyRef): Boolean
-
-
def
nonEmpty: Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
-
def
padTo[A1 >: Sample](len: Int, elem: A1): Iterator[A1]
-
def
partition(p: (Sample) ⇒ Boolean): (Iterator[Sample], Iterator[Sample])
-
def
patch[B >: Sample](from: Int, patchElems: Iterator[B], replaced: Int): Iterator[B]
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def
product[B >: Sample](implicit num: Numeric[B]): B
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def
reduce[A1 >: Sample](op: (A1, A1) ⇒ A1): A1
-
def
reduceLeft[B >: Sample](op: (B, Sample) ⇒ B): B
-
def
reduceLeftOption[B >: Sample](op: (B, Sample) ⇒ B): Option[B]
-
def
reduceOption[A1 >: Sample](op: (A1, A1) ⇒ A1): Option[A1]
-
def
reduceRight[B >: Sample](op: (Sample, B) ⇒ B): B
-
def
reduceRightOption[B >: Sample](op: (Sample, B) ⇒ B): Option[B]
-
def
reversed: List[Sample]
-
def
sameElements(that: Iterator[_]): Boolean
-
-
def
scanLeft[B](z: B)(op: (B, Sample) ⇒ B): Iterator[B]
-
def
scanRight[B](z: B)(op: (Sample, B) ⇒ B): Iterator[B]
-
def
seq: Iterator[Sample]
-
def
size: Int
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def
slice(initial: Sample, direction: DenseVector[Double]): Sample
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def
slice(from: Int, until: Int): Iterator[Sample]
-
def
sliding[B >: Sample](size: Int, step: Int): GroupedIterator[B]
-
def
span(p: (Sample) ⇒ Boolean): (Iterator[Sample], Iterator[Sample])
-
def
stepIn(initial: Sample, direction: DenseVector[Double], logSliceHeight: Double, distanceBounds: (Double, Double)): Sample
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def
stepOut(initial: Sample, logSliceHeight: Double, direction: DenseVector[Double], upperBound: Boolean, offset: Double): Double
-
def
stepSize(stepsTaken: Int, upperBound: Boolean): Double
-
def
sum[B >: Sample](implicit num: Numeric[B]): B
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
-
def
take(n: Int): Iterator[Sample]
-
def
takeWhile(p: (Sample) ⇒ Boolean): Iterator[Sample]
-
def
to[Col[_]](implicit cbf: CanBuildFrom[Nothing, Sample, Col[Sample]]): Col[Sample]
-
def
toArray[B >: Sample](implicit arg0: ClassTag[B]): Array[B]
-
def
toBuffer[B >: Sample]: Buffer[B]
-
def
toIndexedSeq: IndexedSeq[Sample]
-
def
toIterable: Iterable[Sample]
-
def
toIterator: Iterator[Sample]
-
def
toList: List[Sample]
-
def
toMap[T, U](implicit ev: <:<[Sample, (T, U)]): Map[T, U]
-
def
toSeq: Seq[Sample]
-
def
toSet[B >: Sample]: Set[B]
-
def
toStream: Stream[Sample]
-
def
toString(): String
-
def
toTraversable: Traversable[Sample]
-
def
toVector: Vector[Sample]
-
val
uniform: Uniform
-
final
def
wait(): Unit
-
final
def
wait(arg0: Long, arg1: Int): Unit
-
final
def
wait(arg0: Long): Unit
-
def
withFilter(p: (Sample) ⇒ Boolean): Iterator[Sample]
-
def
zip[B](that: Iterator[B]): Iterator[(Sample, B)]
-
def
zipAll[B, A1 >: Sample, B1 >: B](that: Iterator[B], thisElem: A1, thatElem: B1): Iterator[(A1, B1)]
-
def
zipWithIndex: Iterator[(Sample, Int)]
Inherited from Iterator[Sample]
Inherited from TraversableOnce[Sample]
Inherited from GenTraversableOnce[Sample]
Inherited from AnyRef
Inherited from Any
A Monte Carlo Markov Chain for sampling multi-dimensional values given a log-likelihood function over the sample space.