| Year |
Citation |
Score |
| 2020 |
Koslovsky MD, Vannucci M. MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package. Bmc Bioinformatics. 21: 301. PMID 32660471 DOI: 10.1186/S12859-020-03640-0 |
0.323 |
|
| 2020 |
Denti F, Guindani M, Leisen F, Lijoi A, Wadsworth WD, Vannucci M. Two-group Poisson-Dirichlet mixtures for multiple testing. Biometrics. PMID 32535900 DOI: 10.1111/Biom.13314 |
0.4 |
|
| 2020 |
Kook JH, Vaughn KA, DeMaster DM, Ewing-Cobbs L, Vannucci M. BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks. Neuroinformatics. PMID 32504259 DOI: 10.1007/S12021-020-09472-W |
0.408 |
|
| 2020 |
Peterson CB, Osborne N, Stingo FC, Bourgeat P, Doecke JD, Vannucci M. Bayesian modeling of multiple structural connectivity networks during the progression of Alzheimer's disease. Biometrics. PMID 32026459 DOI: 10.1111/Biom.13235 |
0.333 |
|
| 2020 |
Miao Y, Kowal DR, Panchal N, Vila J, Vannucci M. Nonlinear state-space modeling approaches to real-time autonomous geosteering Journal of Petroleum Science and Engineering. 189: 107025. DOI: 10.1016/J.Petrol.2020.107025 |
0.362 |
|
| 2019 |
Cremaschi A, Argiento R, Shoemaker K, Peterson C, Vannucci M. Hierarchical Normalized Completely Random Measures for Robust Graphical Modeling. Bayesian Analysis. 14: 1271-1301. PMID 32431780 DOI: 10.1214/19-Ba1153 |
0.429 |
|
| 2019 |
Cassese A, Zhu W, Guindani M, Vannucci M. A Bayesian Nonparametric Spiked Process Prior for Dynamic Model Selection Bayesian Analysis. 14: 553-572. DOI: 10.1214/18-Ba1116 |
0.39 |
|
| 2019 |
Wu M, Miao Y, Panchal N, Kowal DR, Vannucci M, Vila J, Liang F. Stochastic clustering and pattern matching for real-time geosteering Geophysics. 84: ID13-ID24. DOI: 10.1190/Geo2018-0781.1 |
0.427 |
|
| 2019 |
Argiento R, Cremaschi A, Vannucci M. Hierarchical Normalized Completely Random Measures to Cluster Grouped Data Journal of the American Statistical Association. 115: 318-333. DOI: 10.1080/01621459.2019.1594833 |
0.343 |
|
| 2018 |
Warnick R, Guindani M, Erhardt E, Allen E, Calhoun V, Vannucci M. A Bayesian Approach for Estimating Dynamic Functional Network Connectivity in fMRI Data. Journal of the American Statistical Association. 113: 134-151. PMID 30853734 DOI: 10.1080/01621459.2017.1379404 |
0.347 |
|
| 2018 |
Shaddox E, Peterson CB, Stingo FC, Hanania NA, Cruickshank-Quinn C, Kechris K, Bowler R, Vannucci M. Bayesian inference of networks across multiple sample groups and data types. Biostatistics (Oxford, England). PMID 30590505 DOI: 10.1093/Biostatistics/Kxy078 |
0.39 |
|
| 2018 |
Li Q, Cassese A, Guindani M, Vannucci M. Bayesian Negative Binomial Mixture Regression Models for the Analysis of Sequence Count and Methylation Data. Biometrics. PMID 30125947 DOI: 10.1111/Biom.12962 |
0.372 |
|
| 2018 |
Chiang S, Vankov ER, Yeh HJ, Guindani M, Vannucci M, Haneef Z, Stern JM. Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity. Plos One. 13: e0190220. PMID 29320526 DOI: 10.1371/Journal.Pone.0190220 |
0.344 |
|
| 2017 |
Chiang S, Guindani M, Yeh HJ, Dewar S, Haneef Z, Stern JM, Vannucci M. A Hierarchical Bayesian Model for the Identification of PET Markers Associated to the Prediction of Surgical Outcome after Anterior Temporal Lobe Resection. Frontiers in Neuroscience. 11: 669. PMID 29259537 DOI: 10.3389/Fnins.2017.00669 |
0.307 |
|
| 2017 |
Mo Q, Shen R, Guo C, Vannucci M, Chan KS, Hilsenbeck SG. A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data. Biostatistics (Oxford, England). PMID 28541380 DOI: 10.1093/Biostatistics/Kxx017 |
0.382 |
|
| 2017 |
Kook JH, Guindani M, Zhang L, Vannucci M. NPBayes-fMRI: Non-parametric Bayesian General Linear Models for Single- and Multi-Subject fMRI Data Statistics in Biosciences. 11: 3-21. DOI: 10.1007/S12561-017-9205-0 |
0.376 |
|
| 2017 |
Li Q, Guindani M, Reich BJ, Bondell HD, Vannucci M. A Bayesian mixture model for clustering and selection of feature occurrence rates under mean constraints Statistical Analysis and Data Mining: the Asa Data Science Journal. 10: 393-409. DOI: 10.1002/Sam.11350 |
0.394 |
|
| 2016 |
Chiang S, Guindani M, Yeh HJ, Haneef Z, Stern JM, Vannucci M. Bayesian vector autoregressive model for multi-subject effective connectivity inference using multi-modal neuroimaging data. Human Brain Mapping. PMID 27862625 DOI: 10.1002/Hbm.23456 |
0.394 |
|
| 2016 |
Li Q, Dahl DB, Vannucci M, Joo H, Tsai JW. KScons: A Bayesian Approach for Protein Residue Contact Prediction using the Knob-Socket Model of Protein Tertiary Structure. Bioinformatics (Oxford, England). PMID 27559156 DOI: 10.1093/Bioinformatics/Btw553 |
0.336 |
|
| 2016 |
Trevino V, Cassese A, Nagy Z, Zhuang X, Herbert J, Antzack P, Clarke K, Davies N, Rahman A, Campbell MJ, Guindani M, Bicknell R, Vannucci M, Falciani F. A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells. Plos Computational Biology. 12: e1004884. PMID 27124473 DOI: 10.1371/Journal.Pcbi.1004884 |
0.326 |
|
| 2016 |
Zhang L, Guindani M, Versace F, Engelmann JM, Vannucci M. A spatiotemporal nonparametric Bayesian model of multi-subject fMRI data The Annals of Applied Statistics. 10: 638-666. DOI: 10.1214/16-Aoas926 |
0.334 |
|
| 2016 |
Shaddox E, Stingo FC, Peterson CB, Jacobson S, Cruickshank-Quinn C, Kechris K, Bowler R, Vannucci M. A Bayesian Approach for Learning Gene Networks Underlying Disease Severity in COPD Statistics in Biosciences. 10: 59-85. DOI: 10.1007/S12561-016-9176-6 |
0.349 |
|
| 2015 |
Stingo FC, Swartz MD, Vannucci M. A Bayesian approach to identify genes and gene-level SNP aggregates in a genetic analysis of cancer data. Statistics and Its Interface. 8: 137-151. PMID 28989562 DOI: 10.4310/Sii.2015.V8.N2.A2 |
0.336 |
|
| 2015 |
Fronczyk KM, Guindani M, Hobbs BP, Ng CS, Vannucci M. A Bayesian Nonparametric Approach for Functional Data Classification with Application to Hepatic Tissue Characterization. Cancer Informatics. 14: 151-62. PMID 27279730 DOI: 10.4137/Cin.S31933 |
0.344 |
|
| 2015 |
Chiang S, Cassese A, Guindani M, Vannucci M, Yeh HJ, Haneef Z, Stern JM. Time-dependence of graph theory metrics in functional connectivity analysis. Neuroimage. PMID 26518632 DOI: 10.1016/J.Neuroimage.2015.10.070 |
0.304 |
|
| 2015 |
Peterson CB, Stingo FC, Vannucci M. Joint Bayesian variable and graph selection for regression models with network-structured predictors. Statistics in Medicine. PMID 26514925 DOI: 10.1002/Sim.6792 |
0.405 |
|
| 2015 |
Waters A, Fronczyk K, Guindani M, Baraniuk RG, Vannucci M. A Bayesian Nonparametric Approach for the Analysis of Multiple Categorical Item Responses. Journal of Statistical Planning and Inference. 166: 52-66. PMID 26500388 DOI: 10.1016/J.Jspi.2014.07.004 |
0.39 |
|
| 2015 |
Peterson CB, Stingo FC, Vannucci M. Bayesian Inference of Multiple Gaussian Graphical Models. Journal of the American Statistical Association. 110: 159-174. PMID 26078481 DOI: 10.1080/01621459.2014.896806 |
0.36 |
|
| 2015 |
Cassese A, Guindani M, Antczak P, Falciani F, Vannucci M. A Bayesian model for the identification of differentially expressed genes in Daphnia magna exposed to munition pollutants. Biometrics. 71: 803-11. PMID 25771699 DOI: 10.1111/Biom.12303 |
0.359 |
|
| 2015 |
Zhang L, Guindani M, Vannucci M. Bayesian Models for fMRI Data Analysis. Wiley Interdisciplinary Reviews. Computational Statistics. 7: 21-41. PMID 25750690 DOI: 10.1002/Wics.1339 |
0.384 |
|
| 2015 |
Villagran A, Huerta G, Vannucci M, Jackson CS, Nosedal A. Non-parametric Sampling Approximation via Voronoi Tessellations Communications in Statistics: Simulation and Computation. DOI: 10.1080/03610918.2013.870798 |
0.358 |
|
| 2014 |
Li Q, Dahl DB, Vannucci M, Hyun Joo, Tsai JW. Bayesian model of protein primary sequence for secondary structure prediction. Plos One. 9: e109832. PMID 25314659 DOI: 10.1371/Journal.Pone.0109832 |
0.335 |
|
| 2014 |
Cassese A, Guindani M, Vannucci M. A bayesian integrative model for genetical genomics with spatially informed variable selection. Cancer Informatics. 13: 29-37. PMID 25288877 DOI: 10.4137/Cin.S13784 |
0.4 |
|
| 2014 |
Cassese A, Guindani M, Tadesse MG, Falciani F, Vannucci M. A HIERARCHICAL BAYESIAN MODEL FOR INFERENCE OF COPY NUMBER VARIANTS AND THEIR ASSOCIATION TO GENE EXPRESSION. The Annals of Applied Statistics. 8: 148-175. PMID 24834139 DOI: 10.1214/13-Aoas705 |
0.396 |
|
| 2014 |
Cowley AW, Moreno C, Jacob HJ, Peterson CB, Stingo FC, Ahn KW, Liu P, Vannucci M, Laud PW, Reddy P, Lazar J, Evans L, Yang C, Kurth T, Liang M. Characterization of biological pathways associated with a 1.37 Mbp genomic region protective of hypertension in Dahl S rats. Physiological Genomics. 46: 398-410. PMID 24714719 DOI: 10.1152/Physiolgenomics.00179.2013 |
0.312 |
|
| 2014 |
Zhang L, Guindani M, Versace F, Vannucci M. A spatio-temporal nonparametric Bayesian variable selection model of fMRI data for clustering correlated time courses. Neuroimage. 95: 162-75. PMID 24650600 DOI: 10.1016/J.Neuroimage.2014.03.024 |
0.422 |
|
| 2013 |
Peterson C, Vannucci M, Karakas C, Choi W, Ma L, Maletić-Savatić M. Inferring metabolic networks using the Bayesian adaptive graphical lasso with informative priors. Statistics and Its Interface. 6: 547-558. PMID 24533172 DOI: 10.4310/Sii.2013.V6.N4.A12 |
0.348 |
|
| 2013 |
Allen GI, Peterson C, Vannucci M, Maletić-Savatić M. Regularized Partial Least Squares with an Application to NMR Spectroscopy. Statistical Analysis and Data Mining. 6: 302-314. PMID 24511361 DOI: 10.1002/Sam.11169 |
0.367 |
|
| 2013 |
Stingo FC, Guindani M, Vannucci M, Calhoun VD. An Integrative Bayesian Modeling Approach to Imaging Genetics. Journal of the American Statistical Association. 108. PMID 24298194 DOI: 10.1080/01621459.2013.804409 |
0.355 |
|
| 2013 |
Jeong J, Vannucci M, Ko K. A wavelet-based Bayesian approach to regression models with long memory errors and its application to FMRI data. Biometrics. 69: 184-96. PMID 23379536 DOI: 10.1111/J.1541-0420.2012.01819.X |
0.601 |
|
| 2013 |
Day R, Joo H, Chavan AC, Lennox KP, Chen YA, Dahl DB, Vannucci M, Tsai JW. Understanding the general packing rearrangements required for successful template based modeling of protein structure from a CASP experiment. Computational Biology and Chemistry. 42: 40-8. PMID 23266765 DOI: 10.1016/J.Compbiolchem.2012.10.008 |
0.359 |
|
| 2013 |
Brownlees CT, Vannucci M. A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series Studies in Nonlinear Dynamics and Econometrics. 17: 21-46. DOI: 10.2139/Ssrn.1550253 |
0.337 |
|
| 2012 |
Stingo FC, Vannucci M, Downey G. BAYESIAN WAVELET-BASED CURVE CLASSIFICATION VIA DISCRIMINANT ANALYSIS WITH MARKOV RANDOM TREE PRIORS. Statistica Sinica. 22: 465-488. PMID 24761126 DOI: 10.5705/Ss.2010.141 |
0.388 |
|
| 2012 |
Vannucci M, Stingo FC, Berzuini C. Bayesian Models for Variable Selection that Incorporate Biological Information Bayesian Statistics 9. DOI: 10.1093/acprof:oso/9780199694587.003.0022 |
0.308 |
|
| 2012 |
Lee SH, Lim J, Li E, Vannucci M, Petkova E. Order test for high-dimensional two-sample means Journal of Statistical Planning and Inference. 142: 2719-2725. DOI: 10.1016/J.Jspi.2012.03.001 |
0.326 |
|
| 2011 |
Savitsky T, Vannucci M, Sha N. Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies. Statistical Science : a Review Journal of the Institute of Mathematical Statistics. 26: 130-149. PMID 24089585 DOI: 10.1214/11-Sts354 |
0.422 |
|
| 2011 |
Stingo FC, Chen YA, Tadesse MG, Vannucci M. INCORPORATING BIOLOGICAL INFORMATION INTO LINEAR MODELS: A BAYESIAN APPROACH TO THE SELECTION OF PATHWAYS AND GENES. The Annals of Applied Statistics. 5: 1978-2002. PMID 23667412 DOI: 10.1214/11-Aoas463 |
0.378 |
|
| 2011 |
Joo H, Chavan AG, Day R, Lennox KP, Sukhanov P, Dahl DB, Vannucci M, Tsai J. Near-native protein loop sampling using nonparametric density estimation accommodating sparcity. Plos Computational Biology. 7: e1002234. PMID 22028638 DOI: 10.1371/Journal.Pcbi.1002234 |
0.36 |
|
| 2011 |
Kwon D, Landi MT, Vannucci M, Issaq HJ, Prieto D, Pfeiffer RM. An Efficient Stochastic Search for Bayesian Variable Selection with High-Dimensional Correlated Predictors. Computational Statistics & Data Analysis. 55: 2807-2818. PMID 21686315 DOI: 10.1016/J.Csda.2011.04.019 |
0.597 |
|
| 2011 |
Trevino V, Tadesse MG, Vannucci M, Al-Shahrour F, Antczak P, Durant S, Bikfalvi A, Dopazo J, Campbell MJ, Falciani F. Analysis of normal-tumour tissue interaction in tumours: prediction of prostate cancer features from the molecular profile of adjacent normal cells. Plos One. 6: e16492. PMID 21479216 DOI: 10.1371/Journal.Pone.0016492 |
0.301 |
|
| 2011 |
Stingo FC, Vannucci M. Variable selection for discriminant analysis with Markov random field priors for the analysis of microarray data. Bioinformatics (Oxford, England). 27: 495-501. PMID 21159623 DOI: 10.1093/Bioinformatics/Btq690 |
0.4 |
|
| 2011 |
Preter M, Lee SH, Petkova E, Vannucci M, Kim S, Klein DF. Controlled cross-over study in normal subjects of naloxone-preceding-lactate infusions; respiratory and subjective responses: relationship to endogenous opioid system, suffocation false alarm theory and childhood parental loss. Psychological Medicine. 41: 385-93. PMID 20444308 DOI: 10.1017/S0033291710000838 |
0.488 |
|
| 2010 |
Savitsky T, Vannucci M. Spiked Dirichlet Process Priors for Gaussian Process Models. Journal of Probability and Statistics. 2010: 201489. PMID 23950763 DOI: 10.1155/2010/201489 |
0.392 |
|
| 2010 |
Stingo FC, Chen YA, Vannucci M, Barrier M, Mirkes PE. A BAYESIAN GRAPHICAL MODELING APPROACH TO MICRORNA REGULATORY NETWORK INFERENCE. The Annals of Applied Statistics. 4: 2024-2048. PMID 23946863 DOI: 10.1214/10-Aoas360 |
0.343 |
|
| 2010 |
Guo B, Villagran A, Vannucci M, Wang J, Davis C, Man TK, Lau C, Guerra R. Bayesian estimation of genomic copy number with single nucleotide polymorphism genotyping arrays. Bmc Research Notes. 3: 350. PMID 21192799 DOI: 10.1186/1756-0500-3-350 |
0.324 |
|
| 2010 |
Day R, Lennox KP, Dahl DB, Vannucci M, Tsai JW. Characterizing the regularity of tetrahedral packing motifs in protein tertiary structure. Bioinformatics (Oxford, England). 26: 3059-66. PMID 21047817 DOI: 10.1093/Bioinformatics/Btq573 |
0.311 |
|
| 2010 |
Lennox KP, Dahl DB, Vannucci M, Day R, Tsai JW. A DIRICHLET PROCESS MIXTURE OF HIDDEN MARKOV MODELS FOR PROTEIN STRUCTURE PREDICTION. The Annals of Applied Statistics. 4: 916-942. PMID 21031154 DOI: 10.1214/09-Aoas296 |
0.376 |
|
| 2010 |
Zhu H, Vannucci M, Cox DD. A bayesian hierarchical model for classification with selection of functional predictors. Biometrics. 66: 463-73. PMID 19508236 DOI: 10.1111/J.1541-0420.2009.01283.X |
0.383 |
|
| 2009 |
Kim S, Dahl DB, Vannucci M. Spiked Dirichlet Process Prior for Bayesian Multiple Hypothesis Testing in Random Effects Models. Bayesian Analysis (Online). 4: 707-732. PMID 23950766 DOI: 10.1214/09-Ba426 |
0.599 |
|
| 2009 |
Ko K, Qu L, Vannucci M. WAVELET-BASED BAYESIAN ESTIMATION OF PARTIALLY LINEAR REGRESSION MODELSWITH LONG MEMORY ERRORS. Statistica Sinica. 19: 1463-1478. PMID 23946613 |
0.53 |
|
| 2009 |
Lennox KP, Dahl DB, Vannucci M, Tsai JW. Density Estimation for Protein Conformation Angles Using a Bivariate von Mises Distribution and Bayesian Nonparametrics. Journal of the American Statistical Association. 104: 586-596. PMID 20221312 DOI: 10.1198/Jasa.2009.0024 |
0.356 |
|
| 2009 |
Jayaraman A, Maguire T, Vemula M, Kwon DW, Vannucci M, Berthiaume F, Yarmush ML. Gene Expression Profiling of Long-Term Changes in Rat Liver Following Burn Injury Journal of Surgical Research. 152: 3-17.e2. PMID 18755477 DOI: 10.1016/J.Jss.2007.05.025 |
0.507 |
|
| 2008 |
Kagiampakis I, Jin H, Kim S, Vannucci M, LiWang PJ, Tsai J. Conservation of unfavorable sequence motifs that contribute to the chemokine quaternary state. Biochemistry. 47: 10637-48. PMID 18781776 DOI: 10.1021/Bi702288A |
0.518 |
|
| 2008 |
Kwon D, Vannucci M, Song JJ, Jeong J, Pfeiffer RM. A novel wavelet-based thresholding method for the pre-processing of mass spectrometry data that accounts for heterogeneous noise. Proteomics. 8: 3019-29. PMID 18615428 DOI: 10.1002/Pmic.200701010 |
0.567 |
|
| 2008 |
Ortega F, Sameith K, Turan N, Compton R, Trevino V, Vannucci M, Falciani F. Models and computational strategies linking physiological response to molecular networks from large-scale data. Philosophical Transactions. Series a, Mathematical, Physical, and Engineering Sciences. 366: 3067-89. PMID 18559319 DOI: 10.1098/Rsta.2008.0085 |
0.341 |
|
| 2008 |
Dahl DB, Bohannan Z, Mo Q, Vannucci M, Tsai J. Assessing side-chain perturbations of the protein backbone: a knowledge-based classification of residue Ramachandran space. Journal of Molecular Biology. 378: 749-58. PMID 18377931 DOI: 10.1016/J.Jmb.2008.02.043 |
0.333 |
|
| 2008 |
Lee SH, Lim J, Vannucci M, Petkova E, Preter M, Klein DF. Order-preserving dimension reduction procedure for the dominance of two mean curves with application to tidal volume curves. Biometrics. 64: 931-9. PMID 18177460 DOI: 10.1111/J.1541-0420.2007.00959.X |
0.362 |
|
| 2008 |
Swartz MD, Mo Q, Murphy ME, Lupton JR, Turner ND, Hong MY, Vannucci M. Bayesian variable selection in clustering high-dimensional data with substructure Journal of Agricultural, Biological, and Environmental Statistics. 13: 407-423. DOI: 10.1198/108571108X378317 |
0.388 |
|
| 2008 |
Dahl DB, Mo Q, Vannucci M. Simultaneous inference for multiple testing and clustering via a Dirichlet process mixture model Statistical Modelling. 8: 23-39. DOI: 10.1177/1471082X0700800103 |
0.374 |
|
| 2007 |
Kwon D, Tadesse MG, Sha N, Pfeiffer RM, Vannucci M. Identifying biomarkers from mass spectrometry data with ordinal outcome. Cancer Informatics. 3: 19-28. PMID 19455232 DOI: 10.4137/Cin.S0 |
0.58 |
|
| 2007 |
Kim S, Tsai J, Kagiampakis I, LiWang P, Vannucci M. Detecting protein dissimilarities in multiple alignments using Bayesian variable selection. Bioinformatics (Oxford, England). 23: 245-6. PMID 17105719 DOI: 10.1093/Bioinformatics/Btl566 |
0.532 |
|
| 2006 |
Sha N, Tadesse MG, Vannucci M. Bayesian variable selection for the analysis of microarray data with censored outcomes. Bioinformatics (Oxford, England). 22: 2262-8. PMID 16845144 DOI: 10.1093/Bioinformatics/Btl362 |
0.437 |
|
| 2006 |
Ko K, Vannucci M. Bayesian wavelet-based methods for the detection of multiple changes of the long memory parameter Ieee Transactions On Signal Processing. 54: 4461-4470. DOI: 10.1109/Tsp.2006.881202 |
0.579 |
|
| 2006 |
Kim S, Tadesse MG, Vannucci M. Variable selection in clustering via Dirichlet process mixture models Biometrika. 93: 877-893. DOI: 10.1093/Biomet/93.4.877 |
0.583 |
|
| 2006 |
Ko K, Vannucci M. Bayesian wavelet analysis of autoregressive fractionally integrated moving-average processes Journal of Statistical Planning and Inference. 136: 3415-3434. DOI: 10.1016/J.Jspi.2005.01.010 |
0.598 |
|
| 2006 |
Kwon DW, Ko K, Vannucci M, Reddy ALN, Kim S. Wavelet methods for the detection of anomalies and their application to network traffic analysis Quality and Reliability Engineering International. 22: 953-969. DOI: 10.1002/Qre.781 |
0.558 |
|
| 2005 |
Tadesse MG, Ibrahim JG, Vannucci M, Gentleman R. Wavelet thresholding with bayesian false discovery rate control. Biometrics. 61: 25-35. PMID 15737075 DOI: 10.1111/J.0006-341X.2005.031102.X |
0.366 |
|
| 2005 |
Park CG, Vannucci M, Hart JD. Bayesian methods for wavelet series in single-index models Journal of Computational and Graphical Statistics. 14: 770-794. DOI: 10.1198/106186005X79007 |
0.591 |
|
| 2005 |
Tadesse MG, Sha N, Vannucci M. Bayesian variable selection in clustering high-dimensional data Journal of the American Statistical Association. 100: 602-617. DOI: 10.1198/016214504000001565 |
0.414 |
|
| 2005 |
Vannucci M, Sha N, Brown PJ. NIR and mass spectra classification: Bayesian methods for wavelet-based feature selection Chemometrics and Intelligent Laboratory Systems. 77: 139-148. DOI: 10.1016/J.Chemolab.2004.10.009 |
0.348 |
|
| 2004 |
Sha N, Vannucci M, Tadesse MG, Brown PJ, Dragoni I, Davies N, Roberts TC, Contestabile A, Salmon M, Buckley C, Falciani F. Bayesian variable selection in multinomial probit models to identify molecular signatures of disease stage. Biometrics. 60: 812-9. PMID 15339306 DOI: 10.1111/J.0006-341X.2004.00233.X |
0.4 |
|
| 2004 |
Tadesse MG, Vannucci M, Liò P. Identification of DNA regulatory motifs using Bayesian variable selection. Bioinformatics (Oxford, England). 20: 2553-61. PMID 15117754 DOI: 10.1093/Bioinformatics/Bth282 |
0.321 |
|
| 2004 |
Gabbanini F, Vannucci M, Bartoli G, Moro A. Wavelet packet methods for the analysis of variance of time series with application to crack widths on the Brunelleschi dome Journal of Computational and Graphical Statistics. 13: 639-658. DOI: 10.1198/106186004X2372 |
0.306 |
|
| 2004 |
Kim SS, Narasimha Reddy AL, Vannucci M. Detecting traffic anomalies through aggregate analysis of packet header data Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3042: 1047-1059. DOI: 10.1007/978-3-540-24693-0_86 |
0.332 |
|
| 2003 |
Sha N, Vannucci M, Brown PJ, Trower MK, Amphlett G, Falciani F. Gene selection in arthritis classification with large-scale microarray expression profiles. Comparative and Functional Genomics. 4: 171-81. PMID 18629129 DOI: 10.1002/Cfg.264 |
0.323 |
|
| 2003 |
Lee KE, Sha N, Dougherty ER, Vannucci M, Mallick BK. Gene selection: a Bayesian variable selection approach. Bioinformatics (Oxford, England). 19: 90-7. PMID 12499298 DOI: 10.1093/Bioinformatics/19.1.90 |
0.41 |
|
| 2003 |
Morris JS, Vannucci M, Brown PJ, Carroll RJ. Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis Journal of the American Statistical Association. 98: 573-583. DOI: 10.1198/016214503000000422 |
0.418 |
|
| 2003 |
Vannucci M, Brown PJ, Fearn T. A decision theoretical approach to wavelet regression on curves with a high number of regressors Journal of Statistical Planning and Inference. 112: 195-212. DOI: 10.1016/S0378-3758(02)00333-6 |
0.352 |
|
| 2002 |
Brown PJ, Vannucci M, Fearn T. Bayes model averaging with selection of regressors Journal of the Royal Statistical Society. Series B: Statistical Methodology. 64: 519-536. DOI: 10.1111/1467-9868.00348 |
0.39 |
|
| 2001 |
Brown PJ, Fearn T, Vannucci M. Bayesian Wavelet Regression on Curves with Application to a Spectroscopic Calibration Problem Journal of the American Statistical Association. 96: 398-408. DOI: 10.1198/016214501753168118 |
0.366 |
|
| 2000 |
Lio P, Vannucci M. Wavelet change-point prediction of transmembrane proteins Bioinformatics. 16: 376-382. PMID 10869036 DOI: 10.1093/Bioinformatics/16.4.376 |
0.353 |
|
| 2000 |
Spiegelman CH, Bennett JF, Vannucci M, McShane MJ, Coté GL. A transparent tool for seemingly difficult calibrations: The parallel calibration method Analytical Chemistry. 72: 135-140. PMID 10655645 DOI: 10.1021/Ac990584R |
0.352 |
|
| 1999 |
Vannucci M, Conrradi F. Covariance structure of wavelet coefficients: Theory and models in a Bayesian perspective Journal of the Royal Statistical Society. Series B: Statistical Methodology. 61: 971-986. DOI: 10.1111/1467-9868.00214 |
0.386 |
|
| 1999 |
Brown PJ, Fearn T, Vannucci M. The choice of variables in multivariate regression: A non-conjugate Bayesian decision theory approach Biometrika. 86: 635-648. DOI: 10.1093/Biomet/86.3.635 |
0.368 |
|
| 1998 |
Brown PJ, Vannucci M, Fearn T. Multivariate Bayesian variable selection and prediction Journal of the Royal Statistical Society. Series B: Statistical Methodology. 60: 627-641. DOI: 10.1111/1467-9868.00144 |
0.388 |
|
| 1998 |
Brown PJ, Vannucci M, Fearn T. Bayesian wavelength selection in multicomponent analysis Journal of Chemometrics. 12: 173-182. DOI: 10.1002/(Sici)1099-128X(199805/06)12:3<173::Aid-Cem505>3.0.Co;2-0 |
0.356 |
|
| 1997 |
Vannucci M, Vidakovic B. Preventing the Dirac disaster: Wavelet based density estimation Journal of the Italian Statistical Society. 6: 145-159. DOI: 10.1007/Bf03178909 |
0.325 |
|
| Show low-probability matches. |