scalation
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scalation/scalation/scalation.modeling/scalation.modeling.forecasting/WeightedMovingAverage

WeightedMovingAverage

scalation.modeling.forecasting.WeightedMovingAverage
See theWeightedMovingAverage companion class
object WeightedMovingAverage

The WeightedMovingAverage companion object provides factory methods for the WeightedMovingAverage class.

Attributes

Companion
class
Graph
Supertypes
class Object
trait Matchable
class Any
Self type

Members list

Value members

Concrete methods

def apply(y: VectorD, hh: Int, tRng: Range, hparam: HyperParameter): WeightedMovingAverage

Create a WeightedMovingAverage object.

Create a WeightedMovingAverage object.

Value parameters

hh

the maximum forecasting horizon (h = 1 to hh)

hparam

the hyper-parameters

tRng

the time range, if relevant (time index may suffice)

y

the response vector (time series data)

Attributes

def backcast(y_: VectorD, i: Int): Double

Backcast to predict the value prior to the start (or offset i) of the time series.

Backcast to predict the value prior to the start (or offset i) of the time series.

Value parameters

i

the index offset (defaults to 0)

y

the response vector (time series data), a prefix suffices

Attributes

def weights(q: Int, u: Double): VectorD

Calculate the weight vector used for computing the weighted average. param q the number weights to compute param u factor indicating how much to have linear vs. flat weights

Calculate the weight vector used for computing the weighted average. param q the number weights to compute param u factor indicating how much to have linear vs. flat weights

Attributes

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