Wavelet-Based Clustering for Mixed-Effects Functional Models in High Dimension

Biometrics

Volumn 69, Issue 1, 2013, Pages 31-40

  Giacofci, M ^a   Lambert Lacroix, S ^b   Marot, G ^c,d,e   Picard, F ^f  

^a UNIV GRENOBLE ALPES   (France)

^b LABORATOIRE TIMC IMAG   (France)

^c INRIA RHÔNE ALPES   (France)

^d UNIV LILLE   (France)

^e INRIA   (France)

^f UNIVERSITÉ LYON 1   (France)

Author keywords

Clustering; Functional data; Mixed models; Wavelets

Indexed keywords

MAXIMUM LIKELIHOOD ESTIMATION; RANDOM PROCESSES;

BASED CLUSTERING; CLUSTERINGS; FIXED EFFECTS; FUNCTIONAL DATAS; HIGH-DIMENSIONAL; HIGHER-DIMENSIONAL; MIXED EFFECTS; MIXED MODELING; RANDOM EFFECTS; WAVELET;

CLUSTERING ALGORITHMS;

CLUSTER ANALYSIS; DATA SET; GENOMICS; MASS SPECTROMETRY; RANDOM WALK METHOD; VARIANCE ANALYSIS; WAVELET ANALYSIS;

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; COMPARATIVE GENOMIC HYBRIDIZATION; COMPUTER SIMULATION; FEMALE; GENETICS; HUMAN; MASS SPECTROMETRY; METHODOLOGY; OVARY TUMOR; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; CLUSTER ANALYSIS; COMPARATIVE GENOMIC HYBRIDIZATION; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; LIKELIHOOD FUNCTIONS; MASS SPECTROMETRY; MODELS, STATISTICAL; OVARIAN NEOPLASMS;

EID: 84875955983     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2012.01828.x     Document Type: Article

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