| Year |
Citation |
Score |
| 2017 |
Krafty RT, Rosen O, Stoffer DS, Buysse DJ, Hall MH. Conditional Spectral Analysis of Replicated Multiple Time Series with Application to Nocturnal Physiology. Journal of the American Statistical Association. 112: 1405-1416. PMID 29430069 DOI: 10.1080/01621459.2017.1281811 |
0.368 |
|
| 2012 |
Krafty RT, Xiong S, Stoffer DS, Buysse DJ, Hall M. Enveloping Spectral Surfaces: Covariate Dependent Spectral Analysis of Categorical Time Series. Journal of Time Series Analysis / a Journal Sponsored by the Bernoulli Society For Mathematical Statistics and Probability. 33: 797-806. PMID 24790257 DOI: 10.1111/J.1467-9892.2011.00773.X |
0.4 |
|
| 2012 |
Stoffer DS, Ombao H. Editorial: Special issue on time series analysis in the biological sciences Journal of Time Series Analysis. 33: 701-703. DOI: 10.1111/J.1467-9892.2012.00805.X |
0.318 |
|
| 2012 |
Rosen O, Wood S, Stoffer DS. AdaptSPEC: Adaptive spectral estimation for nonstationary time series Journal of the American Statistical Association. 107: 1575-1589. DOI: 10.1080/01621459.2012.716340 |
0.412 |
|
| 2012 |
Stoffer DS. Frequency Domain Techniques in the Analysis of DNA Sequences Handbook of Statistics. 30: 261-295. DOI: 10.1016/B978-0-444-53858-1.00010-7 |
0.353 |
|
| 2010 |
Stoffer DS, Han S, Qin L, Guo W. Smoothing spline ANOPOW Journal of Statistical Planning and Inference. 140: 3789-3796. DOI: 10.1016/J.Jspi.2010.04.043 |
0.371 |
|
| 2009 |
Rosen O, Stoffer DS, Wood S. Local spectral analysis via a bayesian mixture of smoothing splines Journal of the American Statistical Association. 104: 249-262. DOI: 10.1198/Jasa.2009.0118 |
0.304 |
|
| 2008 |
Kim J, Stoffer DS. Fitting stochastic volatility models in the presence of irregular sampling via particle methods and the em algorithm Journal of Time Series Analysis. 29: 811-833. DOI: 10.1111/J.1467-9892.2008.00584.X |
0.522 |
|
| 2007 |
Koru-Sengul T, Stoffer DS, Day NL. A residuals-based transition model for longitudinal analysis with estimation in the presence of missing data. Statistics in Medicine. 26: 3330-41. PMID 17124699 DOI: 10.1002/Sim.2757 |
0.565 |
|
| 2007 |
Rosen O, Stoffer DS. Automatic estimation of multivariate spectra via smoothing splines Biometrika. 94: 335-345. DOI: 10.1093/Biomet/Asm022 |
0.361 |
|
| 2004 |
Huang HY, Ombao H, Stoffer DS. Discrimination and classification of nonstationary time series using the SLEX model Journal of the American Statistical Association. 99: 763-774. DOI: 10.1198/016214504000001105 |
0.536 |
|
| 2003 |
Stoffer DS. Time series analysis by state space models Automatica. 39: 954-955. DOI: 10.1016/S0005-1098(03)00027-X |
0.343 |
|
| 2002 |
Stoffer DS, Ombao HC, Tyler DE. Local spectral envelope: An approach using dyadic tree-based adaptive segmentation Annals of the Institute of Statistical Mathematics. 54: 201-223. DOI: 10.1023/A:1016182125278 |
0.325 |
|
| 2000 |
Stoffer DS, Tyler DE, Wendt DA. The Spectral Envelope and Its Applications Statistical Science. 15: 224-253. DOI: 10.1214/Ss/1009212816 |
0.405 |
|
| 1999 |
Stoffer DS. Detecting Common Signals in Multiple Time Series Using the Spectral Envelope Journal of the American Statistical Association. 94: 1341-1356. DOI: 10.1080/01621459.1999.10473886 |
0.324 |
|
| 1998 |
Stoffer DS, Tyler DE. Matching sequences: Cross-spectral analysis of categorical time series Biometrika. 85: 201-213. DOI: 10.1093/Biomet/85.1.201 |
0.371 |
|
| 1997 |
McDougall AJ, Stoffer DS, Tyler DE. Optimal transformations and the spectral envelope for real-valued time series Journal of Statistical Planning and Inference. 57: 195-214. DOI: 10.1016/S0378-3758(96)00044-4 |
0.4 |
|
| 1994 |
Stoffer DS, Lutkepohl H, Reinsel GC. Introduction to Multiple Time Series Analysis. Journal of the American Statistical Association. 89: 1138. DOI: 10.2307/2290946 |
0.366 |
|
| 1993 |
Stoffer DS, Tyler DE, Mcdougall AJ. Spectral analysis for categorical time series: Scaling and the spectral envelope Biometrika. 80: 611-622. DOI: 10.1093/Biomet/80.3.611 |
0.416 |
|
| 1992 |
Carlin BP, Polson NG, Stoffer DS. A monte carlo approach to nonnormal and nonlinear state–space modeling Journal of the American Statistical Association. 87: 493-500. DOI: 10.1080/01621459.1992.10475231 |
0.324 |
|
| 1992 |
Stoffer DS, Toloi CMC. A note on the Ljung-Box-Pierce portmanteau statistic with missing data Statistics and Probability Letters. 13: 391-396. DOI: 10.1016/0167-7152(92)90112-I |
0.379 |
|
| 1991 |
Stoffer DS. Walsh-Fourier Analysis and Its Statistical Applications: Rejoinder Journal of the American Statistical Association. 86: 483. DOI: 10.2307/2290599 |
0.312 |
|
| 1991 |
Stoffer DS, Wall KD. Bootstrapping state-space models: Gaussian maximum likelihood estimation and the kalman filter Journal of the American Statistical Association. 86: 1024-1033. DOI: 10.1080/01621459.1991.10475148 |
0.403 |
|
| 1991 |
Shumway RH, Stoffer DS. Dynamic linear models with switching Journal of the American Statistical Association. 86: 763-769. DOI: 10.1080/01621459.1991.10475107 |
0.377 |
|
| 1991 |
Stoffer DS. Walsh–Fourier analysis and its statistical applications Journal of the American Statistical Association. 86: 461-479. DOI: 10.1080/01621459.1991.10475067 |
0.388 |
|
| 1990 |
Stoffer DS. MULTIVARIATE WALSH-FOURIER ANALYSIS Journal of Time Series Analysis. 11: 57-73. DOI: 10.1111/J.1467-9892.1990.Tb00042.X |
0.391 |
|
| 1987 |
Stoffer DS. WALSH-FOURIER ANALYSIS OF DISCRETE-VALUED TIME SERIES Journal of Time Series Analysis. 8: 449-467. DOI: 10.1111/J.1467-9892.1987.Tb00008.X |
0.442 |
|
| 1986 |
Stoffer DS. Estimation and identification of space-time ARMAX models in the presence of missing data Journal of the American Statistical Association. 81: 762-772. DOI: 10.1080/01621459.1986.10478333 |
0.4 |
|
| 1982 |
Shumway RH, Stoffer DS. AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM Journal of Time Series Analysis. 3: 253-264. DOI: 10.1111/J.1467-9892.1982.Tb00349.X |
0.381 |
|
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