Inclusive of SFSU service credit
Pande, A., Majumdar, A., and Kantorowski, L. R. “Equitable Estimation of Accurate High-Injury Networks (HINs) for Vulnerable Road Users.” MTI Publications, 581. (2026). https://doi.org/10.31979/mti.2025.2459.
Muddana, T. K., Bhimreddy, K. S. R., Majumdar, A., and Gupta, R. “Forecasting Gold Returns Volatility Over 1258–2023: The Role of Moments.” Applied Stochastic Models in Business and Industry, 41(5). (2025). https://doi.org/10.1002/asmb.70042.
Gupta, R., Majumdar, A., Pierdzioch, C., and Polat, O. “Climate Risks and Real Gold Returns Over 750 Years.” Forecasting, 6(4), 952–967. (2024). https://doi.org/10.3390/forecast6040047.
Majumdar, A., Lennert-Cody, C. E., Maunder, M. N., and Aires-da-Silva, A. “Spatial-Temporal Modeling for Estimation of Bigeye Tuna Catch in the Presence of Pandemic-Related Data Loss Using Parametric Adjacency Structures.” Fisheries Research, 268. (2023). ISSN 0165-7836.
Majumdar, A., Lennert-Cody, C. E., and Maunder, M. N. “Potential Bias in the 2020 and 2021 Tropical Tuna Catch Estimates Resulting from COVID-19: Update.” Scientific Advisory Committee, IATTC, 14th Meeting. (2023).
Wang, J., Majumdar, A., and Lin, J. “Predictive and Sensitive Analysis of a Bivariate Skewed Spatial Process Based on the Bayesian Framework.” Stat, 12(2). (2023).
Lennert-Cody, C. E., Maunder, M. N., and Majumdar, A. “The Effect of Pandemic-Related Port-Sampling Data Loss on the 2020 Purse-Seine Catch Estimate of Bigeye Tuna in Floating-Object Sets.” Scientific Advisory Committee, IATTC, 13th Meeting. (2022).
Majumdar, A., Lennert-Cody, C. E., Maunder, M. N., and Aires-da-Silva, A. “Identifying and Correcting the Purse-Seine Fleet Catch for Bias Caused by the Pandemic in 2020–2021.” Scientific Advisory Committee, IATTC, 13th Meeting. (2022).
Majumdar, A. “Temporal Case Study of Tagore’s Song Counts by Melodic Styles, Rhythms, and Themes.” Journal of the Indian Statistical Association. (2022).
Sen, R., Majumdar, A., and Sikaria, S. “Bayesian Testing of Granger Causality in Functional Time Series.” Journal of Quantitative Economics, 20(Suppl. 1), 191–210. (2022). https://doi.org/10.1007/s40953-022-00306-x.
Gupta, R., Majumdar, A., Pierdzioch, C., Polat, O. “Climate Risks and Real Gold Returns Over 750 Years.” Forecasting, 6(4), 952–967. (2024). https://doi.org/10.3390/forecast6040047.
Gupta, R., Majumdar, A., Nel, J., and Subramaniam, S. “Geopolitical Risks and the High-Frequency Movements of the US Term Structure of Interest Rates.” Annals of Financial Economics, 16(3). (2021).
Bouri, E., Gupta, R., Majumdar, A., and Subramaniam, S. “Time-Varying Risk Aversion and the Forecastability of the Term Structure of Interest Rates of the United States.” Finance Research Letters, 42. (2021).
Prior to SFSU service credit
Majumdar, A. “Tagore’s Song Counts by Thematic and Nonthematic Classifications: A Statistical Case Study.” Sankhya B, 1–36. (2019).
Chang, T., Gupta, R., Majumdar, A., and Pierdzioch, C. “Predicting Stock Market Movements with a Time-Varying Consumption-Aggregate Wealth Ratio.” International Review of Economics and Finance, 59(C), 458–467. (2019).
Eyden, R., Balcilar, M., Gupta, R., Thompson, K., and Majumdar, A. “Comparing the Forecasting Ability of Financial Conditions Indices: The Case of South Africa.” Quarterly Review of Economics and Finance, 69, 245–259. (2018).
Wang, J., Yang, M., and Majumdar, A. “Comparative Study and Sensitivity Analysis of Skewed Spatial Processes.” Computational Statistics, 33(1), 75–98. (2018).
Gupta, R., Majumdar, A., and Wohar, M. E. “The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence from a Quantile Predictive Regression Approach.” Open Economies Review, 28(1), 47–59. (2017).
Gupta, R., Majumdar, A., Pierdzioch, C., and Wohar, M. E. “Do Terror Attacks Predict Gold Returns? Evidence from a Quantile-Predictive-Regression Approach.” Quarterly Review of Economics and Finance, 65, 276–284. (2017).
Wang, J., Yang, M., and Majumdar, A. “Package DZEXPM: Estimation and Prediction of Skewed Spatial Processes.” CRAN Library. (2017).
Paul, D., and Majumdar, A. “Discussion on ‘Of Quantiles and Expectiles: Consistent Scoring Functions, Choquet Representations and Forecast Rankings,’ by Werner Ehm, Tilmann Gneiting, Alexander Jordan, and Fabian Kruger.” Journal of the Royal Statistical Society, Series B, 78. (2016).
Yang, M., Das, K., and Majumdar, A. “Analysis of Bivariate Zero-Inflated Regression Counts with Missing Responses.” Journal of Multivariate Analysis, 148(C), 73–82. (2016).
Bekiros, S., Gupta, R., and Majumdar, A. “Incorporating Economic Policy Uncertainty in US Equity Premium Models: A Nonlinear Predictability Analysis.” Finance Research Letters, 18, 291–296. (2016).
McHale, M., Hall, S., Majumdar, A., and Grimm, N. B. “Carbon Lost vs. Carbon Gained in an Arid City: A Study of Vegetation and the Associated Carbon Tradeoffs Among Land Uses in Phoenix, Arizona.” Ecological Applications, 27(2), 644–661. (2016).
Majumdar, A., and Paul, D. “Zero Expectile Processes and Bayesian Spatial Regression.” Journal of Computational and Graphical Statistics, 25(3), 72–747. (2016).
Eberle, D., Das, S., and Majumdar, A. “Automated Pattern Recognition to Support Geological Mapping and Exploration Target Generation: A Case Study from Southern Namibia.” Journal of African Earth Sciences, 106, 60–74. (2015).
Gupta, R., and Majumdar, A. “Forecasting US Real House Price Returns, 1831–2013: Evidence from Copula Models.” Applied Economics, 47(48), 5204–5213. (2015).
Gupta, R., Balcilar, M., Majumdar, A., and Miller, S. “Was the Recent Downturn in US GDP Predictable?” Applied Economics, 47(28), 2985–3007. (2015).
Majumdar, A. “Gaussian Processes on the Support of Cylindrical Surfaces, with Application to Periodic Spatio-Temporal Data.” Journal of Statistical Planning and Inference, 153, 27–41. (2014).
Aye, G. C., Gupta, R., Balcilar, M., and Majumdar, A. “Forecasting Aggregate Retail Sales: The Case of South Africa.” International Journal of Production Economics, 160, 66–79. (2015).
Gupta, R., and Majumdar, A. “Reconsidering the Welfare Cost of Inflation in the US: A Nonparametric Estimation of the Nonlinear Long-Run Money Demand Equation Using Projection Pursuit Regressions.” Empirical Economics, 46(4), 1221–1240. (2014).
Zhong, Z., Majumdar, A., and Eubank, R. L. “Bayesian Curve Registration of Functional Data.” In Statistical Paradigms: Recent Advances and Reconciliations, edited by A. SenGupta, T. Samanta, and A. Basu, 181–210. (2014).
Gupta, R., Balcilar, M., Majumdar, A., and Miller, S. “Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes.” Empirical Economics, 44(2), 387–417. (2013).
Majumdar, A., Gries, C., and Walker, J. “A Non-Stationary Spatial Generalized Linear Mixed Model Approach for Studying Plant Diversity.” Journal of Applied Statistics, 38(1), 1935–1950. (2011).
Majumdar, A. “Review on Tagore by Fireside by Mayetri Devi.” Journal of Humanistic Ideology, 3(2), 163–167. (2010).
Majumdar, A., Paul, D., and Kaye, J. “Sensitivity Analysis and Model Selection with a Generalized Convolution for Spatial Processes.” Bayesian Analysis, 5(3), 493–518. (2010).
Majumdar, A., and Gries, C. “Bivariate Zero-Inflated Regression for Count Data: A Bayesian Approach with Application to Plant Counts.” International Journal of Biostatistics, 6(1), Article 27. (2010).
Majumdar, A., Paul, D., and Bautista, D. “Generalized Convolution Models for Nonstationary Multivariate Spatial Processes.” Statistica Sinica, 20, 675–695. (2010).
Majumdar, A., and Eubank, R. “A Bayesian Semi-Parametric Approach to Modeling and the Analysis of Texas Lottery Sales.” Journal of Data Science, 7(1), 73–87. (2009).
Majumdar, A., and Eubank, R. “Bayesian Modeling of Functional Data with Application to the Texas Lottery.” JSM Proceedings, Bayesian Statistical Science Section. Alexandria, VA: American Statistical Association. (2008).
Kaye, J., Majumdar, A., Gries, C., Buyantuyev, A., Grimm, N. B., Hope, D., Zhu, W., Jenerette, D., and Baker, L. “Hierarchical Bayesian Scaling of Soil Properties Across Urban, Agricultural, and Desert Ecosystems.” Ecological Applications, 18(1), 132–145. (2008).
Majumdar, A., Kaye, J., Gries, C., Hope, D., and Grimm, N. “Hierarchical Spatial Modeling of Soil Nutrients and Carbon in Heterogeneous Land-Use Patches of the Phoenix Metropolitan Area.” Communications in Statistics: Simulation and Computation, 37(2), 434–453. (2007).
Majumdar, A., and Gelfand, A. E. “Multivariate Spatial Modeling for Geostatistical Data Using Convolved Covariance Functions.” Mathematical Geology, 39(2), 225–245. (2007).
Majumdar, A., Munneke, H., Gelfand, A. E., Banerjee, S., and Sirmans, C. F. “Gradients in Spatial Response Surfaces with Applications to Land-Value Prices.” Journal of Business and Economic Statistics, 24(1), 77–90. (2006).
Majumdar, A., Gelfand, A. E., and Banerjee, S. “Spatio-Temporal Change-Point Modeling.” Journal of Statistical Planning and Inference, Herman Chernoff: Eightieth Birthday Felicitation Volume, 130(1–2), 149–166. (2004).
Baguley, L., Majumdar, A., Das, S., Mangisa, S., and Balcilar, M. “Are Winters Getting Shorter and Warmer? A Generalized Additive Modeling Perspective.”
Masum, M., Bhimreddy, K. S. R., Chavanpatil, P., and Majumdar, A. “Binge Drinking, Frequent Mental Distress, and the Alcohol Harm Paradox: Variation by Race, Ethnicity, and Sex Among US Adults, 2013 to 2023.”
Kite, C., and Majumdar, A. “Assessing and Mapping Demographic Disparities with Traffic Stop Data.”
Sen, R., Dutta, D., and Majumdar, A. “Testing Change-Point for Functional Data.”
Majumdar, A. “Shrinkage Priors for Bayesian Inference: A Brief Contextual Survey.”
CRAN Library: DZEXPM package by J. Wang, M. Yang, and A. Majumdar.