PointsUpdate {adlift}

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)

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).

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.

Value

coeff

vector of (modified) detail and scaling coefficients to be used in the next step of the transform.

lengths

the vector of interval lengths after the update step of the transform.

r

the index into pointsin of remove.

N

length(pointsin).

weights

The regression coefficients used in prediction.

alpha

the update weights used to update lengths and coeff.

Author(s)

Matt Nunes ([e-mail]), Marina Knight

See Also

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

Examples

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