"aws"
The "aws"
class is
used for objects obtained by functions aws
, lpaws
, aws.irreg
and aws.gaussian
.
Objects are created by calls to functions aws
, lpaws
, aws.irreg
and aws.gaussian
.
.Data
:Object of class "list"
, usually empty.
y
:Object of class "array"
containing the original (response) data
dy
:Object of class "numeric"
dimension attribute of y
nvec
:Object of class "integer"
leading dimension of y
in vector valued data.
x
:Object of class "numeric"
if provided the design points
ni
:Object of class "numeric"
sum of weights used in final estimate
mask
:Object of class "logical"
mask of design points where computations are performed
theta
:Object of class "array"
containes the smoothed object and in case
of function lpaws
its derivatives up to the specified degree.
Dimension is dim(theta)=c(dy,p)
hseq
:Sequence of bandwidths employed.
mae
:Object of class "numeric"
Mean absolute error with respect to
array in argument u
if provided.
psnr
:Object of class "numeric"
Peak Signal to Noise Ratio (PSNR) with respect to
array in argument u
if provided.
var
:Object of class "numeric"
pointwise variance of
theta[...,1]
xmin
:Object of class "numeric"
min of x
in case of irregular design
xmax
:Object of class "numeric"
max of x
in case of irregular design
wghts
:Object of class "numeric"
weights used in location penalty for
different coordinate directions, corresponds to ratios of distances in coordinate directions 2 and 3 to
and distance in coordinate direction 1.
degree
:Object of class "integer"
degree of local polynomials used in
function lpaws
hmax
:Object of class "numeric"
maximal bandwidth
sigma2
:Object of class "numeric"
estimated error variance
scorr
:Object of class "numeric"
estimated spatial correlation
family
:Object of class "character"
distribution of y
,
can be any of c("Gaussian","Bernoulli","Poisson","Exponential",
"Volatility","Variance")
shape
:Object of class "numeric"
possible shape parameter of distribution of y
lkern
:Object of class "integer"
location kernel, can be
any of c("Triangle","Quadratic","Cubic","Plateau","Gaussian")
, defauts to
"Triangle"
lambda
:Object of class "numeric"
scale parameter used in adaptation
ladjust
:Object of class "numeric"
factor to adjust scale parameter with respect to its
predetermined default.
aws
:Object of class "logical"
Adaptation by Propagation-Separation
memory
:Object of class "logical"
Adaptation by Stagewise Aggregation
homogen
:Object of class "logical"
detect regions of homogeneity (used to speed up
the calculations)
earlystop
:Object of class "logical"
further speedup in function lpaws
estimates are fixed if sum of weigths does not increase with iterations.
varmodel
:Object of class "character"
variance model used in
function aws.gaussian
vcoef
:Object of class "numeric"
estimates variance parameters
in function aws.gaussian
call
:Object of class "call"
that created the object.
signature(x = "aws")
: ...
signature(y = "aws")
: ...
Method for Function `plot' in Package `aws'.
Method for Function `show' in Package `aws'.
Method for Function `print' in Package `aws'.
Method for Function `summary' in Package `aws'.
Joerg Polzehl, polzehl@wias-berlin.de
Joerg Polzehl, Vladimir Spokoiny, Adaptive Weights Smoothing with applications to image restoration, J. R. Stat. Soc. Ser. B Stat. Methodol. 62 , (2000) , pp. 335--354
Joerg Polzehl, Vladimir Spokoiny, Propagation-separation approach for local likelihood estimation, Probab. Theory Related Fields 135 (3), (2006) , pp. 335--362.
aws
, lpaws
, aws.irreg
, aws.gaussian