Certificate of Merit award in recognition of superior academic achievement in the Department of Mathematical Sciences, Northern Illinois University.
ARTICLES PUBLISHED/UNDER REVISION
Dhar, S. S., Kundu, D., & Das, U. (near completion in 2020). Inspecting Structural Changes of Chirp Signal Model.
Das U. and Das K. Selection of influential variables in ordinal data with preponderance of zeros. Under Review.
Dhar, S. S., Kundu, D., & Das, U. (2019). Tests For the Parameters of Chirp Signal Model. IEEE Transactions on Signal Processing, 67(16), 4291-4301.
Mitra, D., Das, U., & Das, K. (2019). Analysis of interval-censored competing risks data under missing causes. Journal of Applied Statistics, 1-21.
Lahiri, S.N., Das, U. & Nordman, D.J. (2019). Empirical Likelihood for a long range dependent process subordinated to a Gaussian process. Accepted in Journal of Time Series Analysis.
Das, U., & Das, K. (2018). Inference on zero inflated ordinal models with semiparametric link. Computational Statistics & Data Analysis, 128, 104-115.
Das, U., Dhar, S. S., & Pradhan, V. (2018). Corrected likelihood-ratio tests in logistic regression using small-sample data. Communications in Statistics-Theory and Methods, 47(17), 4272-4285.
Das, U., & Ebrahimi, N. (2018). A new method for covariate selection in Cox model. Statistics in Transition New Series. VOLUME 19 , ISSUE 2 , Pages 297-314.
Das, U., & Ebrahimi, N. (2017). Covariate selection for accelerated failure time data. Communications in Statistics-Theory and Methods, 46(8), 4051-4064.
Das, Ujjwal. "Variable Selection for Survival Data under Weibull Distribution." Calcutta Statistical Association Bulletin 68.1-2 (2016): 52-68.
"Bias Reduction in Logistic Regression with Missing Responses when the Missing Data Mechanism is Nonignorable" by Maity A.K., Pradhan V. and Das, U. Accepted in "The American Statistician" doi 10.1080/00031305.2017.1407359.
Das, U., Gupta, S., & Gupta, S. (2014). Screening active factors in supersaturated designs. Computational Statistics & Data Analysis, 77, 223-232.
Foulkes A., Matthews G.,Das, U., Ferguson J., Lin R., Reilly M. (2013), Mixed Modeling of Meta-Analysis P-Values (MixMAP) Suggests Multiple Novel Gene Loci for Low Density Lipoprotein Cholesterol. PLoS ONE 8(2): e54812. doi:10.1371/journal.pone.0054812.
Pradhan, V., Menon, S. and Das U. (2013),Corrected profile likelihood confidence interval for binomial paired incomplete data. Pharmaceutical Statistics, vol 12: 48 - 58.
Das U., Maiti T, and Pradhan V (2010). Bias correction of the logistic regression with missing categorical covariates. Journal of Statistical Planning and Inference, vol. 140: 2478 - 2485.
Dhar S. S. and Das U. On Distance Based Goodness of Fit Tests for Missing Data when Missing Occurs at Random. Provisionally accepted in Australian & New Zealand Journal of Statistics.