Description Usage Arguments Details Value Note Author(s) References See Also Examples
Function of a time series x returning its unbalanced Haar wavelet expansion, as obtained with a bottom-up algortithm. BUUHWE is an acronym for Bottom-Up Unbalanced Haar Wavelets Expansion.
1 2 3 | BUUHWE(x)
Breakpoints(Dataset.BUUHWE)
Details(Dataset.BUUHWE)
|
x |
a numeric vector of length N |
Dataset.BUUHWE |
a list of outputs of |
See BAGIDIS-package
for an overview about the BAGIDIS methodology and References for details, in particular Timmermans (2012), Chapter 1, Timmermans and von Sachs (2010) or Fryzlewicz (2007).
BUUHWE(x)
returns a list with
detail |
detail coefficients starting from rank k=0 up to k=N-1. |
basis |
unbalanced Haar basis vectors ordered by colums. First column is the constant vector of rank k=0. This is a matrix of dimensions N xN. |
split.abs |
localization index. For consistency with basis matrix and detail vector dimensions, this is a vector of length N but first coefficient is |
series |
the initial series |
Breakpoints
returns the breakpoints of the Unbalanced Haar wavelet basis, from rank k=1 to rank k=N-1. In case it is applied to a list of BUUHWE provided for M series of length N, it returns the breakpoints for each elements of the list, as a matrix with M columns and N-1 rows.
Details
returns the details of the Unbalanced Haar wavelet basis, from rank k=1 to rank k=N-1. In case it is applied to a list of outputs of BUUHWE
provided for M series of length N, it returns the details for each elements of the list, as a matrix with M columns and N-1 rows.
This function can be compared to function uh.bu
in package unbalhaar of Piotr Fryzlewicz. Nevertheless outputs are differents as uh.bu
is intented for denoising. The unbalanced Haar basis expansion is thus not explicitely obtained in uh.bu
. Function BUUHWE.plot
provides with a representation of the unbalanced Haar basis expansion.
Function BUUHWE_2D
is the image equivalent of BUUHWE
.
The BUUHWE expansion is the starting step for comparing curves through the BAGIDIS semi-distance. See function semimetric.BAGIDIS
.
Breakpoints and details define what is called the signature of the series in the b-d plane. See references for details. A representation of the signature is obtained with BD.plot
.
Catherine Timmermans, Institute of Statistics, Biostatistics and Actuarial Sciences, UCLouvain, Belgium.
Contact: catherine.timmermans@uclouvain.be
The main references are
Timmermans C., 2012, Bases Giving Distances. A new paradigm for investigating functional data with applications for spectroscopy. PhD thesis, Universite catholique de Louvain. http://hdl.handle.net/2078.1/112451
Timmermans C. and von Sachs R., 2015, A novel semi-distance for investigating dissimilarities of curves with sharp local patterns, Journal of Statistical Planning and Inference, 160, 35-50. http://hdl.handle.net/2078.1/154928
Fryzlewicz P. and Timmermans C., 2015, SHAH: Shape Adaptive Haar wavelets for image processing. Journal of Computational and Graphical Statistics. (accepted - published online 27 May 2015) http://stats.lse.ac.uk/fryzlewicz/shah/shah.pdf
Timmermans C., Delsol L. and von Sachs R., 2013, Using BAGIDIS in nonparametric functional data analysis: predicting from curves with sharp local features, Journal of Multivariate Analysis, 115, p. 421-444. http://hdl.handle.net/2078.1/118369
Other references include
Girardi M. and Sweldens W., 1997, A new class of unbalanced Haar wavelets that form an unconditional basis for Lp on general measure spaces, J. Fourier Anal. Appl. 3, 457-474
Fryzlewicz P., 2007, Unbalanced Haar Technique for Non Parametric Function Estimation, Journal of the American Statistical Association, 102, 1318-1327.
Timmermans C., von Sachs, R. , 2010, BAGIDIS, a new method for statistical analysis of differences between curves with sharp patterns (ISBA Discussion Paper 2010/30). Url : http://hdl.handle.net/2078.1/91090
Timmermans, C. , Fryzlewicz, P., 2012, SHAH: Shape-Adaptive Haar Wavelet Transform For Images With Application To Classification (ISBA Discussion Paper 2012/15). Url: http://hdl.handle.net/2078.1/110529
semimetric.BAGIDIS
, BUUHWE.plot
, BUUHWE_2D
,BD.plot
.
1 2 3 4 5 | x= c(1,7,3,0,-2,6,4,0,2)
BUUHWE(x)
Breakpoints(list(BUUHWE(x)))
y= c(1,7,5,5,-2,1,4,0,2)
Breakpoints(list(BUUHWE(x),BUUHWE(y)))
|
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