(PhD STUDENT (working under my supervision) : *, BS-MS/MSc STUDENT (working under my supervision) : **)
Topological Data Analysis :
Kumar, S.* and Dhar, S. S. (2025+) Testing Homological Equivalence Using Betti Numbers : Probabilistic Properties. To appear in SIAM : Theory of Probability and Its Applications / Teoriya Veroyatnostei i ee Primeneniya (Russian version). Supplementary materials
Quantiles Based Methods:
Dhar, S. S. and Wu, W. (2023) Comparing time varying regression quantiles under shift invariance. Bernoulli, 29, 1527--1554.
Dutta, D. **, Dhar, S. S. and Mitra, A. (2019) On Quantile Estimator in Volatility Model with Non- negative Error Density and Bayesian Perspective. Advances in Econometrics, 40B, 193–210. (Remark : It is part of "Econometrics" as well).
Dhar, S. S., Chakraborty, B. and Chaudhuri, P. (2014) Comparison of Multivariate Distributions Using Quantile-Quantile Plots and Related Tests. Bernoulli, 20, 1484–1506.
Non-parameric Regression Methods (Finite Dimensional) :
Bagchi, P. and Dhar, S. S. (2024) Characterization of the least squares estimator : mis-specified multivariate isotonic regression model with dependent errors. AMS :Theory of Probability and Mathematical Statistics / Teoriya Veroyatnosteĭ i Matematicheskaya Statistika (Russian version) , 110, 143--158
Dhar, S. S., Jha, P. * and Rakshit, P. ** (2022) The Trimmed Mean in Non-parametric Regression Function Estimation. AMS : Theory of Probability and Mathematical Statistics / Teoriya Veroyatnosteĭ i Matematicheskaya Statistika (Russian version), 107, 133--158.
(Invited article) Shalabh and Dhar, S. S. (2021) Goodness of Fit in Non-parametric Regression Modelling. Journal of Statistical Theory and Practice. (Invited article for the special issue dedicated to Professor C.R. Rao on “Celebrating the Centenary of Professor C R Rao”), 15, Article number : 18.
Dette, H., Dhar, S. S. and Wu, W. (2021) Identifying Shifts between Two Regression Curves. Annals of the Institute of Statistical Mathematics, 73, 855–889.
Bagchi, P. and Dhar, S. S. (2020) A Study on the Least Squares Estimator of Multivariate Isotonic Regression Function. Scandinavian Journal of Statistics, 47, 1192–1221.
Dhar, S. S., Bergsma, W. and Dassios, A. (2018) Testing Independence of Covariates and Errors in Nonparametric Regression. Scandinavian Journal of Statistics, 45, 421–443.
Dhar, S. S. (2016) Trimmed Mean Isotonic Regression. Scandinavian Journal of Statistics, 43, 202–212.
Robust Statistical Methods (Finite Dimensional) :
(Invited article) Dhar, S. S., Shalabh, Aayush ** and Das, H. S.** (2025+) A New Graphical Device based on Trimmed Mean. To appear in Journal of Statistical Research. (Invited article in honour of Professor A K Md E Saleh).
(Invited article) Dhar, S. S., Chatterjee, U.** (not affiliated with IIT Kanpur) and Shalabh (2022) A Note on Asymptotic Distribution of Trimmed mean. Journal of the Indian Society for Probability and Statistics (Invited article for the special issue of the 40th Convention of ISPS), 23, 327--335.
Chakraborty, C. * and Dhar, S. S. (2020) A Test for Multivariate Location Parameter in Elliptical Model based on Forward Search Method. Sankhya, Series A, 82, 68–95.
Dhar, S. S., Dassios, A. and Bergsma, W. (2016) A Study of the Power and Robustness of a New Test for Independence against Contiguous Alternatives. Electronic Journal of Statistics, 10, 330–351.
Dhar, S. S. and Chaudhuri, P. (2012) On the Derivatives of the Trimmed Mean. Statistica Sinica, 22, 655-679.
Dhar, S. S. and Chaudhuri, P. (2011) On Statistical Efficiency of Robust Estimators of Multivariate Location. Statistical Methodology, 8, 113–128.
Dhar, S. S. and Chaudhuri, P. (2009) A Comparison of Robust Estimators Based on Two Types of Trimming. Advances in Statistical Analysis, 93, 151–158.
Econometrics:
(Invited article) Shukla, S.*, Dhar, S. S. and Shalabh (2025+) Applications of Nonlinear Tobit Models Under Endogeneity. To appear in Sankhya, Series B (Invited article in honour of Professor CR Rao).
Dutta, D. **, Dhar, S. S. and Mitra, A. (2019) On Quantile Estimator in Volatility Model with Non- negative Error Density and Bayesian Perspective. Advances in Econometrics, 40B, 193–210.
Statistical Applications:
Shalabh, Dhar, S. S. and Rajeshbhai, S. P. ** (2024+) Statistical Data-Driven Modelling and Forecasting: An Application to COVID-19 Pandemic. To appear in Annals of Data Science.
Dhar, S. S. and Shalabh. (2022) GIVE Statistic for Goodness of Fit in Instrumental Variables Models with Application to COVID Data. Nature Scientific Reports. 12, Article number : 9472.
Statistical Signal Processing:
Dhar, S. S., Kundu, D. and Das, U. (2019) Tests for the Parameters of Chirp Signal Model. IEEE Transactions on Signal Processing, 67, 4291–4301.
Statistical Epidemiology:
Ghosh, S., Banerjee, M., Dhar, S. S., Mukhopadhyay, S. (2025) Estimation of time-varying recovery and death rates from epidemiological data: A new approach. Mathematical Biosciences, 387, 109479.
Miscellaneous Topics :
Dhar, S. S. and Das, U. (2021) On distance based goodness of fit Tests for missing data when missing occurs at random. Australian & New Zealand Journal of Statistics, 63, 331–356.
Trafimow, D., Amrhein, V., Areshenko C. N., Barrera-Causil, C., Beh, E. J., Bilgi, Y., Bono, R., Bradley, M. T., Briggs, W. M., Cepeda-Freyre, H. A., Chaigneau, S. E., Ciocca, D. R., Correa, J. C., Cousineau, D., de Boer, M. R., Dhar, S. S., Dolgov, I., Gmez-Benito, J., Grendar, M., Grice, J., Guerrero-Gimenez, M. E., Gutirrez, A., Huedo-Medina, T. B., Jae, K., Janyan, A., Karimnezhad, A., Korner- Nievergelt, F., Kosugi, K., Lachmair, M., Ledesma, R., Limongi, R., Liuzza, M. T., Lombardo, R., Marks, M., Meinlschmidt, G., Nalborczyk, L., Nguyen, H. T., Ospina, R., Perezgonzalez, J. D., Pfister, R., Rahona, J. J., Rodrguez-Medina, D. A., Romo, X., Ruiz-Fernndez, S., Suarez, I., TegethoM., Tejo, M., van de Schoot, R., Vankov, I., Velasco-Forero, S., Wang, T., Yamada, Y., Zoppino, F. C. M., and Marmolejo-Ramos, F. (2018) Manipulating the Alpha Level Cannot Cure Significance Testing. Frontiers in Psychology, 9, Article 699.
Das, U., Dhar, S. S. and Pradhan, V. (2018) Lilelihood Ratio Tests in Logistic Regression for Separated Data. Communication in Statistics: Theory and Methods, 47, 4272–4285.
Møllersen, K., Dhar, S. S. and Godtliebsen, F. (2016) On Desirable Properties for Density Based Dissimilarity Measures in Hybrid Clustering. Applied Mathematics, 7, 1674–1706.