Research
Published Research
(Titles link to the Scholars at Duke Repository, while DOIs link to the publisher's site if available. Not all publications may be listed here. Let me know if you cannot find something!)- Li, Y., & Clyde, M. A. (2018). Mixtures of g-priors in Generalized Linear Models. Journal of the American Statistical Association, 113(524), 1828–1845. https://doi.org/10.1080/01621459.2018.146999210.1080/01621459.2018.1469992
- Day, D. B., Clyde, M. A., Xiang, J., Li, F., Cui, X., Mo, J., … Zhang, J. J. (2018). Age modification of ozone associations with cardiovascular disease risk in adults: a potential role for soluble P-selectin and blood pressure.. Journal of Thoracic Disease, 10(7), 4643–4652. https://doi.org/10.21037/jtd.2018.06.13510.21037/jtd.2018.06.135
- Day, D. B., Xiang, J., Mo, J., Clyde, M. A., Weschler, C. J., Li, F., … Zhang, J. (2018). Combined use of an electrostatic precipitator and a high-efficiency particulate air filter in building ventilation systems: Effects on cardiorespiratory health indicators in healthy adults.. Indoor Air, 28(3), 360–372. https://doi.org/10.1111/ina.1244710.1111/ina.12447
- Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E.-J., Berk, R., … Johnson, V. E. (2018). Redefine statistical significance.. Nature Human Behaviour, 2(1), 6–10. https://doi.org/10.1038/s41562-017-0189-z10.1038/s41562-017-0189-z
- RE: “RISK PREDICTION FOR EPITHELIAL OVARIAN CANCER IN 11 UNITED STATES–BASED CASE-CONTROL STUDIES: INCORPORATION OF EPIDEMIOLOGIC RISK FACTORS AND 17 CONFIRMED GENETIC LOCI”. (2017). American Journal of Epidemiology, 186(1), 130–130. https://doi.org/10.1093/aje/kwx15110.1093/aje/kwx151
- Ness, R., Clyde, M., Palmieri, R., & Schildkraut, J. (2017). Risk prediction for ovarian cancer: epidemiologic risk factors plus confirmed genetic loci. In Bjog an International Journal of Obstetrics and Gynaecology (Vol. 124, pp. 159–159). WILEY.
- Clyde, M. A., Palmieri Weber, R., Iversen, E. S., Poole, E. M., Doherty, J. A., Goodman, M. T., … , on behalf of the Ovarian Cancer Association Consortium. (2016). Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.. Am J Epidemiol, 184(8), 579–589. https://doi.org/10.1093/aje/kww09110.1093/aje/kww091
- Clyde, M. A., Weber, R. P., Ness, R., & Schildkraut, J. (2016). RISK PREDICTION FOR OVARIAN CANCER: EPIDEMIOLOGIC RISK FACTORS PLUS CONFIRMED GENETIC LOCI. In International Journal of Gynecological Cancer (Vol. 26, pp. 28–28). LIPPINCOTT WILLIAMS & WILKINS.
- Chou, N. D., Serafini, S., Grant, G. A., Clyde, M., Komisarow, J., & Muh, C. R. (2016). 127 Multimodality Word-Finding Distinctions in Pediatric Cortical Stimulation Mapping.. Neurosurgery, 63(CN_suppl_1). https://doi.org/10.1227/01.neu.0000489697.88290.8810.1227/01.neu.0000489697.88290.88
- Chou, N. D., Serafini, S., Grant, G. A., Clyde, M., Komisarow, J., & Muh, C. R. (2016). 127 Multimodality Word-Finding Distinctions in Pediatric Cortical Stimulation Mapping.. Neurosurgery, 63 Suppl 1. https://doi.org/10.1227/01.neu.0000489697.88290.8810.1227/01.neu.0000489697.88290.88
- Clyde, M. A. (2016). BAS: Bayesian Model Averaging using Bayesian Adaptive Sampling. CRAN. https://doi.org/10.5281/zenodo.5949710.5281/zenodo.59497
- Clyde, M. A. (2015). Experimental Design: Bayesian Designs. In International Encyclopedia of the Social & Behavioral Sciences: Second Edition (pp. 521–526). https://doi.org/10.1016/B978-0-08-097086-8.42121-510.1016/B978-0-08-097086-8.42121-5
- Clyde, M. A. (2015). Experimental Design: Bayesian Designs. In International Encyclopedia of the Social & Behavioral Sciences: Second Edition (pp. 521–526). https://doi.org/10.1016/B978-0-08-097086-8.42121-510.1016/B978-0-08-097086-8.42121-5
- Serafini, S., Clyde, M. A., Husain, A. M., & Haglund, M. M. (2015). Brain Mapping and Monitoring. In A. M. Husain (Ed.), Practical Epilepsy (pp. 192–199). Demos Medical Publishing, LLC.
- Iversen, E. S., Lipton, G., Clyde, M. A., & Monteiro, A. N. A. (2014). Functional Annotation Signatures of Disease Susceptibility Loci Improve SNP Association Analysis. Bmc Genomics, 15, 398–398. https://doi.org/10.1186/1471-2164-15-39810.1186/1471-2164-15-398
- Serafini, S., Clyde, M., Tolson, M., & Haglund, M. M. (2013). Multimodality word-finding distinctions in cortical stimulation mapping.. Neurosurgery, 73(1), 36–47. https://doi.org/10.1227/01.neu.0000429861.42394.d810.1227/01.neu.0000429861.42394.d8
- Clydec, M., & Iversen, E. S. (2013). Bayesian model averaging in the M-open framework. In Bayesian Theory and Applications (pp. 483–498). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199695607.003.002410.1093/acprof:oso/9780199695607.003.0024
- Clyde, M. A., & Ghosh, J. (2012). Finite population estimators in stochastic search variable selection. Biometrika, 99(4), 981–988. https://doi.org/10.1093/biomet/ass04010.1093/biomet/ass040
- Loredo, T. J., Berger, J. O., Chernoff, D. F., Clyde, M. A., & Liu, B. (2012). Bayesian methods for analysis and adaptive scheduling of exoplanet observations. Statistical Methodology, 9(1–2), 101–114. https://doi.org/10.1016/j.stamet.2011.07.00510.1016/j.stamet.2011.07.005
- Ghosh, J., & Clyde, M. A. (2011). Rao-blackwellization for Bayesian variable selection and model averaging in linear and binary regression: A novel data augmentation approach. Journal of the American Statistical Association, 106(495), 1041–1052. https://doi.org/10.1198/jasa.2011.tm1051810.1198/jasa.2011.tm10518
- Clyde, M. A., Ghosh, J., & Littman, M. L. (2011). Bayesian adaptive sampling for variable selection and model averaging. Journal of Computational and Graphical Statistics, 20(1), 80–101. https://doi.org/10.1198/jcgs.2010.0904910.1198/jcgs.2010.09049
- Clyde, M. A., & Wolpert, R. L. (2011). Discussion of ``Polson and Scott: Shrink globally, act locally: Sparse Bayesian regularization and prediction''. In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 9 (pp. 528–529). Oxford University Press.
- Wolpert, R. L., Clyde, M. A., & Tu, C. (2011). Stochastic expansions using continuous dictionaries: Lévy adaptive regression kernels. Annals of Statistics, 39(4), 1916–1962. https://doi.org/10.1214/11-AOS88910.1214/11-AOS889
- Armagan, A., Dunson, D. B., & Clyde, M. A. (2011). Generalized Beta Mixtures of Gaussians. Advances in Neural Information Processing Systems, 24, 523–531.
- House, L. L., Clyde, M. A., & Wolpert, R. L. (2011). Bayesian nonparametric models for peak identification in MALDI-TOF mass spectroscopy. The Annals of Applied Statistics, 5(2B), 1488–1511. https://doi.org/10.1214/10-AOAS45010.1214/10-AOAS450
- Clyde, M. A., & Wolpert, R. L. (2011). Discussion of ``Polson and Scott: Shrink globally, act locally: Sparse Bayesian regularization and prediction''. In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 9 (pp. 528–529). Oxford University Press.
- Wilson, M. A., Iversen, E. S., Clyde, M. A., Schmidler, S. C., & Schildkraut, J. M. (2010). BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES.. Ann Appl Stat, 4(3), 1342–1364.
- Schildkraut, J. M., Iversen, E. S., Wilson, M. A., Clyde, M. A., Moorman, P. G., Palmieri, R. T., … Berchuck, A. (2010). Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer.. Plos One, 5(4). https://doi.org/10.1371/journal.pone.001006110.1371/journal.pone.0010061
- Jesneck, J. L., Mukherjee, S., Yurkovetsky, Z., Clyde, M., Marks, J. R., Lokshin, A. E., & Lo, J. Y. (2009). Do serum biomarkers really measure breast cancer?. Bmc Cancer, 9. https://doi.org/10.1186/1471-2407-9-16410.1186/1471-2407-9-164
- Schildkraut, J., Iversen, E., Marks, J., Wilson, M., Clyde, M., Palmieri, R., … Berchuck, A. (2009). Association between serous invasive ovarian cancer and variants in candidate DNA damage response genes. Cancer Research, 69.
- Schildkraut, J. M., Goode, E. L., Clyde, M. A., Iversen, E. S., Moorman, P. G., Berchuck, A., … Australian Ovarian Cancer Study Group. (2009). Single nucleotide polymorphisms in the TP53 region and susceptibility to invasive epithelial ovarian cancer.. Cancer Res, 69(6), 2349–2357. https://doi.org/10.1158/0008-5472.CAN-08-290210.1158/0008-5472.CAN-08-2902
- Zhou, X. K., Clyde, M. A., Garrett, J., Lourdes, V., O’Connell, M., Parmigiani, G., … Wiles, T. (2009). Statistical methods for automated drug susceptibility testing: Bayesian minimum inhibitory concentration prediction from growth curves. Annals of Applied Statistics, 3(2), 710–730. https://doi.org/10.1214/08-AOAS21710.1214/08-AOAS217
- Chu, J. H., Clyde, M. A., & Liang, F. (2009). Bayesian function estimation using continuous wavelet dictionaries. Statistica Sinica, 19(4), 1419–1438.
- Palmieri, R. T., Wilson, M. A., Iversen, E. S., Clyde, M. A., Calingaert, B., Moorman, P. G., … Australian Ovarian Cancer Study Group. (2008). Polymorphism in the IL18 gene and epithelial ovarian cancer in non-Hispanic white women.. Cancer Epidemiol Biomarkers Prev, 17(12), 3567–3572. https://doi.org/10.1158/1055-9965.EPI-08-054810.1158/1055-9965.EPI-08-0548
- Liang, F., Paulo, R., Molina, G., Clyde, M. A., & Berger, J. O. (2008). Mixtures of g priors for Bayesian variable selection. Journal of the American Statistical Association, 103(481), 410–423. https://doi.org/10.1198/01621450700000133710.1198/016214507000001337
- Clyde, M. A., & Wolpert, R. L. (2007). Nonparametric Function Estimation using Overcomplete Dictionaries (with Discussion). In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 8 (pp. 91–114). Oxford University Press.
- Clyde, M. A., Berger, J. O., Bullard, F., Ford, E. B., Jefferys, W. H., Luo, R., … Loredo, T. (2007). Current challenges in Bayesian model choice. Statistical Challenges in Modern Astronomy Iv, 371, 224–240.
- Clyde, M. A., & Wolpert, R. L. (2007). Nonparametric Function Estimation using Overcomplete Dictionaries (with Discussion). In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 8 (pp. 91–114). Oxford University Press.
- Kuncel, A. M., Cooper, S. E., Wolgamuth, B. R., Clyde, M. A., Snyder, S. A., Montgomery, E. B., … Grill, W. M. (2006). Clinical response to varying the stimulus parameters in deep brain stimulation for essential tremor.. Movement Disorders : Official Journal of the Movement Disorder Society, 21(11), 1920–1928. https://doi.org/10.1002/mds.2108710.1002/mds.21087
- Clyde, M. A., House, L., & Wolpert, R. L. (2006). Nonparametric Models for Proteomic Peak Identification and Quantification. In K.-A. Do, P. Müller, & M. Vannucci (Eds.), Bayesian Inference for Gene Expression and Proteomics (pp. 293–308). Cambridge University Press.
- Clyde, M., House, L., Tu, C., & Wolpert, R. L. (2005). Bayesian Nonparametric Function Estimation Using Overcomplete Representations and Levy Random Field Priors. Oberwolfach Reports, 2(4), 2628–2633. https://doi.org/10.4171/OWR/2005/4710.4171/OWR/2005/47
- House, L., Clyde, M. A., & Huang, Y. C. (2005). Bayesian Identification of Differential Gene Expression Induced by Metals in Human Bronchial Epithelial Cells. Bayesisan Analysis, 1(1), 105–120. https://doi.org/10.1214/06-BA10310.1214/06-BA103
- Goodman, A. M., Clyde, M. A., Burdick, D. S., Idriss, S. F., & Wolf, P. D. (2004). Minimum energy single-shock internal atrial defibrillation in sheep.. J Interv Card Electrophysiol, 10(2), 131–138. https://doi.org/10.1023/B:JICE.0000019266.09648.f610.1023/B:JICE.0000019266.09648.f6
- Clyde, M., & George, E. I. (2004). Model uncertainty. Statistical Science, 19(1), 81–94. https://doi.org/10.1214/08834230400000003510.1214/088342304000000035
- Lee, H. K. H., & Clyde, M. A. (2004). Lossless online Bayesian bagging. Journal of Machine Learning Research, 5, 143–151.
- Dominici, F., Sheppard, L., & Clyde, M. (2003). Health effects of air pollution: A statistical review. International Statistical Review, 71(2), 243–276.
- Clyde, M. (2003). Model Averaging. In S. J. Press (Ed.), Subjective and Objective Bayesian Statistics: Principles, Models, and Applications. John Wiley & Sons.
- Clyde, M. (2003). Invited discussion of "Bayesian and Frequentist Multiple Testing, by C. Genovese and L. Wasserman". In J. M. Bernardo, M. J. Bayarri, A. P. Dawid, J. O. Berger, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 7 (pp. 157–160). Oxford University Press.
- Clyde, M. A., & George, E. I. (2003). Invited discussion of ``Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis'' by J.S. Morris, M. Vannucci, P.J. Brown, and R.J. Carroll.. Journal of the American Statistical Association, 98(463), 584–585. https://doi.org/10.1198/01621450300000044010.1198/016214503000000440
- Clyde, M., & Chaloner, K. (2002). Constrained design strategies for improving normal approximations in nonlinear regression problems. Journal of Statistical Planning and Inference, 104(1), 175–196. https://doi.org/10.1016/S0378-3758(01)00239-710.1016/S0378-3758(01)00239-7
- Clyde, M. A. (2001). Experimental Design: Bayesian Designs. In International Encyclopedia of the Social & Behavioral Sciences (pp. 5075–5081). Elsevier. https://doi.org/10.1016/b0-08-043076-7/00421-610.1016/b0-08-043076-7/00421-6
- Clyde, M., & Lee, H. K. (2001). Bagging and the Bayesian Bootstrap. Artificial Intelligence and Statistics, 8, 169–174.
- Clyde, M. (2001). Discussion of Hugh Chipman, Edward I. George and Robert E. McCulloch, "The Practical Implementation of Bayesian Model Selection". In Institute of Mathematical Statistics Lecture Notes - Monograph Series (pp. 117–124). Institute of Mathematical Statistics. https://doi.org/10.1214/lnms/121554096510.1214/lnms/1215540965
- Clyde, M. (2000). Model uncertainty and health effect studies for particulate matter. Environmetrics, 11(6), 745–763. https://doi.org/10.1002/1099-095X(200011/12)11:6<745::AID-ENV431>3.0.CO;2-N10.1002/1099-095X(200011/12)11:6<745::AID-ENV431>3.0.CO;2-N
- Clyde, M., & George, E. I. (2000). Flexible empirical Bayes estimation for wavelets. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 62(4), 681–698. https://doi.org/10.1111/1467-9868.0025710.1111/1467-9868.00257
- Dominici, F., Parmigiani, G., & Clyde, M. (2000). Conjugate analysis of multivariate normal data with incomplete observations. Canadian Journal of Statistics, 28(3), 533–550. https://doi.org/10.2307/331596310.2307/3315963
- Lamon, E. C., & Clyde, M. A. (2000). Accounting for model uncertainty in prediction of chlorophyll a in Lake Okeechobee. Journal of Agricultural, Biological, and Environmental Statistics, 5(3), 297–322. https://doi.org/10.2307/140045610.2307/1400456
- Clyde, M. (1999). Comment. Statistical Science, 14(4), 401–404.
- MacEachern, S. N., Clyde, M., & Liu, J. S. (1999). Sequential importance sampling for nonparametric Bayes models: The next generation. Canadian Journal of Statistics, 27(2), 251–267. https://doi.org/10.2307/331563710.2307/3315637
- Clyde, M. A. (1999). Bayesian Model Averaging and Model Search Strategies (with Discussion). In J. M. Bernardo, A. P. Dawid, J. O. Berger, & A. F. M. Smith (Eds.), Bayesian Statistics 6 (Vol. 6, pp. 157–185). Oxford University Press.
- Clyde, M. A. (1999). Comment on ``Bayesian Model Averaging: A Tutorial'' by Hoeting, JA., Madigan,D., Raftery, AE., and Volinsky, CT.. Statistical Science, 14, 401–404. https://doi.org/10.1214/ss/100921251910.1214/ss/1009212519
- Paddock, S., West, M., Young, S. S., & Clyde, M. (1999). Mixture Models in the Exploration of Structure-Activity Relationships in Drug Design. In Case Studies in Bayesian Statistics (pp. 339–353). Springer New York. https://doi.org/10.1007/978-1-4612-1502-8_910.1007/978-1-4612-1502-8_9
- Clyde, M. A., & George, E. I. (1999). Empirical Bayes Estimation in Wavelet Nonparametric Regression. In Bayesian Inference in Wavelet-Based Models (pp. 309–322). Springer New York. https://doi.org/10.1007/978-1-4612-0567-8_1910.1007/978-1-4612-0567-8_19
- Clyde, M. A., & Parmigiani, G. (1998). Protein construct storage: Bayesian variable selection and prediction with mixtures.. Journal of Biopharmaceutical Statistics, 8(3), 431–443. https://doi.org/10.1080/1054340980883525110.1080/10543409808835251
- Clyde, M., Parmigiani, G., & Vidakovic, B. (1998). Multiple shrinkage and subset selection in wavelets. Biometrika, 85(2), 391–401. https://doi.org/10.1093/biomet/85.2.39110.1093/biomet/85.2.391
- Clyde, M. A. (1997). Strategies for Model Mixing in Generalized Linear Models. Artificial Intelligence and Statistics, 6, 103–114.
- Clyde, M. A., Parmigiani, G., & Vidakovic, B. (1997). Using Markov chain Monte Carlo to account for model uncertainty, with applications to wavelets. In L. Billard & N. I. Fisher (Eds.), Computing science and statistics. (Vol. 28, pp. 209–218). Fairfax Station, VA: Interface Foundation of North America,.
- Clyde, M. A. (1997). Strategies for Model Mixing in Generalized Linear Models. Artificial Intelligence and Statistics, 6, 103–114.
- Clyde, M. A., Parmigiani, G., & Vidakovic, B. (1997). Using Markov chain Monte Carlo to account for model uncertainty, with applications to wavelets. In L. Billard & N. I. Fisher (Eds.), Computing science and statistics. (Vol. 28, pp. 209–218). Fairfax Station, VA: Interface Foundation of North America,.
- Clyde, M., & Chaloner, K. (1996). The equivalence of constrained and weighted designs in multiple objective design problems. Journal of the American Statistical Association, 91(435), 1236–1244. https://doi.org/10.1080/01621459.1996.1047699310.1080/01621459.1996.10476993
- Clyde, M. A., Muller, P., & Parmigiani, G. (1996). Inference and design strategies for a hierarchical logistic regression model. In D. A. Berry & D. K. Stangl (Eds.), Bayesian Biostatistics (Vol. 151, pp. 297–320). New York, NY: Marcel Dekker.
- Clyde, M., & Parmigiani, G. (1996). Orthogonalizations and Prior Distributions for Orthogonalized Model Mixing. In Modelling and Prediction Honoring Seymour Geisser (pp. 206–227). Springer New York. https://doi.org/10.1007/978-1-4612-2414-3_1310.1007/978-1-4612-2414-3_13
- Clyde, M. A., DeSimone, H., & Parmigiani, G. (1996). Prediction via orthogonalized model mixing. Journal of the American Statistical Association, 91, 1197–1208. https://doi.org/10.2307/229173810.2307/2291738
- Clyde, M. A., Muller, P., & Parmigiani, G. (1996). Inference and design strategies for a hierarchical logistic regression model. In D. A. Berry & D. K. Stangl (Eds.), Bayesian Biostatistics (Vol. 151, pp. 297–320). New York, NY: Marcel Dekker.
- Clyde, M. A. (1995). Bayesian Designs for Approximate Normality. In C. P. Kitsos & W. G. Muller (Eds.), MODA 4 -- Advances in Model--Oriented Data Analysis (pp. 25–35). Physica-Verlag. https://doi.org/10.1007/978-3-662-12516-810.1007/978-3-662-12516-8
- Clyde, M., Müller, P., & Parmigiani, G. (1995). Optimal Design for Heart Defibrillators. In Lecture Notes in Statistics (pp. 278–292). Springer New York. https://doi.org/10.1007/978-1-4612-2546-1_710.1007/978-1-4612-2546-1_7
- Clyde, M., DeSimone, H., & Parmigiani, G. (1995). Discussion of "Accounting for Model Uncertainty in Survival Analysis Improves Predictive Performance by A.E. Raftery, D.M. Madigan and C.T. Volinsky". In J. O. Berger, J. M. Bernardo, A. P. Dawid, & A. F. M. Smith (Eds.), Bayesian Statistics 5 (Vol. 5, pp. 341–341). Oxford University Press.
- Clyde, M. A., DeSimone, H., & Parmigiani, G. (1994). A Comparison of Algorithms for Sampling Models. In Proceedings of the 1994 Joint Statistical Meetings; Section on Bayesian Statistical Science (pp. 211–216).
- Furnier, G. R., Stine, M., Mohn, C. A., & Clyde, M. A. (1991). Geographic patterns of variation in allozymes and height growth in white spruce. Canadian Journal of Forest Research, 21(5), 707–712. https://doi.org/10.1139/x91-09710.1139/x91-097
- Clyde, M., & Strauss, D. (1991). Logistic regression for spatial pair-potential models. In Institute of Mathematical Statistics Lecture Notes - Monograph Series (pp. 14–30). Institute of Mathematical Statistics. https://doi.org/10.1214/lnms/121546049010.1214/lnms/1215460490
- Clyde, M., & Strauss, D. (1991). Logistic regression for spatial pair-potential models. In Institute of Mathematical Statistics Lecture Notes - Monograph Series (pp. 14–30). Institute of Mathematical Statistics. https://doi.org/10.1214/lnms/121546049010.1214/lnms/1215460490
- Furnier, G. R., Knowles, P., Clyde, M. A., & Dancik, B. P. (1987). Effects of avian seed dispersal on the genetic structure of whitebark pine populations.. Evolution, 41(3), 607–612.
- Clyde, M. A. (1987). Radial and longitudinal variation in stem diameter increment of lodgepole pine, white spruce, and black spruce: species and crown class differences. Canadian Journal of Forest Research, 1223–1227.
- Clyde, M. A. (1987). A new computerized system for tree ring measurement and analysis. Forestry Chronicle, 63, 23–27.
- Clyde, M. A., House, L. L., Wolpert, R. L., & Vannucci, M. (n.d.). Nonparametric Models for Proteomic Peak Identification and Quantification. In Bayesian Inference for Gene Expression and Proteomics (pp. 293–308). Cambridge University Press. https://doi.org/10.1017/cbo9780511584589.01610.1017/cbo9780511584589.016