Professor of Statistics
Indian Institute of Technology Kanpur (India)
Shalabh is a professor of Statistics at Indian Institute of Technology Kanpur (India). He has more than 20 years of experience in teaching and research. He has authored and co-authored more than 75 research papers and four books including a book with Prof. C.R. Rao. His main areas of research are linear regression analysis, econometrics, linear models, measurement error models etc. He has been awarded several national and international awards and fellowships like Jan Tinbergen award from International Statistical Institute (The Netherlands), National award in Statistics (India), Mahalanobis Memorial Medal – National Award (India), Alexander von Humboldt fellowship (Germany).
Principal Investigator | Administration
Research interest in relevance of the project
- Regression analysis
- Visualization of data
- Bayesian analysis
Field of Expertise
- Regression analysis, Econometrics
- Forecasting techniques
- Sampling theory
- C.L. Cheng, Shalabh and G. Garg (2016) : “Goodness of Fit in Restricted Measurement Error Models”, Journal of Multivariate Analysis, 145, pp. 101-116.
- C.L. Cheng, Shalabh and G. Garg (2014): “Coefficient of Determination for Multiple Measurement Error Models”, Journal of Multivariate Analysis, 123, pp. 137-152.
- A.K.Md.E. Saleh and Shalabh (2014): “Ridge Regression Estimation Approach to Measurement Error Model”, Journal of Multivariate Analysis, 123, pp. 68-84.
- Shalabh, G. Garg and C. Heumann (2012): “Performance of Double k-class Estimators for Coefficients in Linear Regression Models with Non Spherical Disturbances under Asymmetric Losses”, Journal of Multivariate Analysis, 112, pp. 35-47.
- Shalabh, Gaurav Garg and Neeraj Misra (2009): “Use of Prior Information in the Consistent Estimation of Regression Coefficients in a Measurement Error Model”, Journal of Multivariate Analysis, Vol. 100, pp. 1498-1520.
Complete list of publications
Department of Mathematics and Statistics
Indian Institute of Technology
Kanpur – 208016
Phone: +91 512 2597636