Anandamayee Majumdar
Anandamayee Majumdar
Inter-American Tropical Tuna Commission
Verified email at - Homepage
Cited by
Cited by
Multivariate spatial modeling for geostatistical data using convolved covariance functions
A Majumdar, AE Gelfand
Mathematical Geology 39 (2), 225-245, 2007
Incorporating economic policy uncertainty in US equity premium models: A nonlinear predictability analysis
S Bekiros, R Gupta, A Majumdar
Finance Research Letters 18, 291-296, 2016
Forecasting aggregate retail sales: The case of South Africa
GC Aye, M Balcilar, R Gupta, A Majumdar
International Journal of Production Economics 160, 66-79, 2015
Hierarchical Bayesian scaling of soil properties across urban, agricultural, and desert ecosystems
JP Kaye, A Majumdar, C Gries, A Buyantuyev, NB Grimm, D Hope, ...
Ecological Applications 18 (1), 132-145, 2008
Do terror attacks predict gold returns? Evidence from a quantile-predictive-regression approach
R Gupta, A Majumdar, C Pierdzioch, ME Wohar
The Quarterly Review of Economics and Finance 65, 276-284, 2017
Spatio-temporal change-point modeling
A Majumdar, AE Gelfand, S Banerjee
Journal of Statistical Planning and Inference 130 (1-2), 149-166, 2005
Gradients in spatial response surfaces with application to urban land values
A Majumdar, HJ Munneke, AE Gelfand, S Banerjee, CF Sirmans
Journal of Business & Economic Statistics 24 (1), 77-90, 2006
A generalized convolution model for multivariate nonstationary spatial processes
A Majumdar, D Paul, D Bautista
Statistica Sinica, 675-695, 2010
Bivariate zero-inflated regression for count data: A Bayesian approach with application to plant counts
A Majumdar, C Gries
The international journal of biostatistics 6 (1), 2010
Comparing the forecasting ability of financial conditions indices: The case of South Africa
M Balcilar, R Gupta, R Van Eyden, K Thompson, A Majumdar
The Quarterly Review of Economics and Finance 69, 245-259, 2018
Hierarchical spatial modeling and prediction of multiple soil nutrients and carbon concentrations
A Majumdar, J Kaye, C Gries, D Hope, N Grimm
Communications in Statistics—Simulation and Computation« 37 (2), 434-453, 2008
Forecasting US real house price returns over 1831–2013: evidence from copula models
R Gupta, A Majumdar
Applied Economics 47 (48), 5204-5213, 2015
Automated pattern recognition to support geological mapping and exploration target generation–A case study from southern Namibia
D Eberle, D Hutchins, S Das, A Majumdar, H Paasche
Journal of African Earth Sciences 106, 60-74, 2015
Carbon lost and carbon gained: a study of vegetation and carbon trade‐offs among diverse land uses in P hoenix, Arizona
MR McHale, SJ Hall, A Majumdar, NB Grimm
Ecological Applications 27 (2), 644-661, 2017
Was the recent downturn in US real GDP predictable?
M Balcilar, R Gupta, A Majumdar, SM Miller
Applied Economics 47 (28), 2985-3007, 2015
Reconsidering the welfare cost of inflation in the US: a nonparametric estimation of the nonlinear long-run money-demand equation using projection pursuit regressions
R Gupta, A Majumdar
Empirical Economics 46 (4), 1221-1240, 2014
Forecasting Nevada gross gaming revenue and taxable sales using coincident and leading employment indexes
M Balcilar, R Gupta, A Majumdar, SM Miller
Empirical Economics 44 (2), 387-417, 2013
The Role of current account balance in forecasting the US equity premium: Evidence from a quantile predictive regression approach
R Gupta, A Majumdar, ME Wohar
Open Economies Review 28 (1), 47-59, 2017
Spatial modeling for multivariate environmental data using convolved covariance functions
A Majumdar, AE Gelfand
Technical Report Institute of Statistics and Decision Sciences, Dukeá…, 2006
Zero expectile processes and Bayesian spatial regression
A Majumdar, D Paul
Journal of Computational and Graphical Statistics 25 (3), 727-747, 2016
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