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adlift (version 0.8-2)

PointsUpdate: PointsUpdate

Description

This function performs the update lifting step using a given configuration of neighbours and boundary handling.

Usage

PointsUpdate(X, coeff, nbrs, index, remove, pointsin, weights, lengths,
 updateboundhandl)

Arguments

X
the vector of grid values.
coeff
the vector of detail and scaling coefficients at that step of the transform.
nbrs
the indices (into X) of the neighbours to be used in the lifting step.
index
the indices into pointsin of nbrs, the neighbours of remove.
remove
the index (into X) of the point to be removed.
pointsin
The indices of gridpoints still to be removed.
weights
the prediction weights obtained from the regression in the prediction step of the transform.
lengths
the vector of interval lengths at the present step of the transform (to be updated).
updateboundhandl
boundary handling in the update step. Possible values are "reflect", "stop" and "add". If the point to be removed is at the boundary, "reflect" updates the neighbour interval to be symmetrical about its

Value

  • coeffvector of (modified) detail and scaling coefficients to be used in the next step of the transform.
  • lengthsthe vector of interval lengths after the update step of the transform.
  • rthe index into pointsin of remove.
  • Nlength(pointsin).
  • weightsThe regression coefficients used in prediction.
  • alphathe update weights used to update lengths and coeff.

Details

The procedure performs a minimum norm update lifting step. Firstly the interval lengths are updated using the coefficients obtained. Secondly, the scaling and detail coefficient vector is modified using the new interval lengths.

See Also

AdaptNeigh, AdaptPred, CubicPred, fwtnp, LinearPred, QuadPred, UndoPointsUpdate

Examples

Run this code
#
# Generate some blocks data: 100 observations.
#
x <- runif(100)
y <-make.signal2("blocks",x=x)
#
#find initial interval lengths...
#
I<-intervals(x,"reflect")
l<-lengthintervals(x,I$intervals,neighbours=2,closest=FALSE)
lengths<-l$lengths
#
#perform prediction step...
p<-AdaptNeigh(order(x),x,y,32,5,TRUE,2)
#
#
u<-PointsUpdate(x,p$results[[6]],p$newinfo[[3]],p$newinfo[[4]],5,order(x),p$results[[4]],
lengths,"add")
#
#and here are the updated coefficients...
u$coeff
#

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