Shalabh
shalab@iitk.ac.in
shalabh1@yahoo.com
Department of Mathematics & Statistics
Indian Institute of Technology Kanpur, Kanpur - 208016 (India)

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Books

1. Title: Introduction to Statistics and Data Analysis     - With Exercises, Solutions and Applications in R     (Second edition)     Authors: Christian Heumann, Michael Schomaker and Shalabh     Publisher: Springer, 2022   Access and download the book at SpringerLink- Click Here   Course webpage:  https://statsbook.github.io/
2. Title: Introduction to Statistics and Data Analysis             - With Exercises, Solutions and Applications in R     (First edition)     Authors: Christian Heumann, Michael Schomaker and Shalabh     Publisher: Springer, 2016   More than 5.39 Million downloads    Number of downloads   Access and download the book at SpringerLink- Click Here Course webpage:  http://chris.userweb.mwn.de/book/
3. Title: Statistical Analysis of Designed Experiments     Authors: H. Toutenburg and Shalabh     Publisher: Springer, 2010   Access and download the book at SpringerLink- Click Here
4. Title: Linear Models and Generalizations - Least Squares and Alternatives     Authors: C.R. Rao, H. Toutenburg, Shalabh, and C. Heumann     Publisher: Springer, 2008   Access and download the book at SpringerLink- Click Here   Reprinted by Beijing World Publishing Corporation

5. Title: Recent Advances In Linear Models and Related Areas      Editors: Shalabh and C. Heumann      Publisher: Springer, 2008   Access and download the book at SpringerLink- Click Here

 

Research Papers

 

120. Subhra Sankar Dhar and Shalabh: "M-Estimation of Functional Regression Operator with Responses Missing at Random" in Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making. Volume I , Editors: Irfan Ali, Umar Muhammad Modibbo, Asaju La'aro Bolaji, Harish Garg, Taylor's & Francis, CRC Press (Accepted for publication).

119. Christian Heumann and Shalabh: "James--Stein Estimator in Regression and Econometric Models'' in International Encyclopedia of Statistical Science, Springer (Accepted for publication).

118.  Shalabh and Subhra Sankar Dhar: "Data Analytics with R - A Motivational Foundation and Beginning" in Recent Advances in Simulation and Modelling, Editors: Mohd. Arshad, Mukti Khetan, Ashok Kumar Pathak, Fozia Homa, Taylor's & Francis, CRC Press (Accepted for publication).

117.  Shalabh, Subhra Sankar Dhar and Gaurav Garg: "Robust Measures of Goodness of Fit and Outlier Detection in Linear Regression Models" in Statistical Outliers and Related Topics, Editors: Mir Masoom Ali, Irfan Ali, and Haitham M. Yousof, Taylor's & Francis, CRC Press (Accepted for publication).

116.  Anoop Chaturvedi and Shalabh: "Minimum Risk Predictors in Linear Regression Model" in Recent Advances in Simulation and Modelling, Editors: Mohd. Arshad, Mukti Khetan, Ashok Kumar Pathak, Fozia Homa, Taylor's & Francis, CRC Press (Accepted for publication).

115. Subhra Sankar Dhar, Shalabh, Prashant Jha, and Aranyak Acharyya: "Variable Selection in Multiple Nonparametric Regression Modelling" in Advanced Mathematical Techniques Applicable in Computational and Intelligent Systems, Editors: Sandeep Singh, Aliakbar Montazer Haghighi, and Sandeep Dalal, Taylor's & Francis, CRC Press (Accepted for publication).

114. Shalabh, Subhra Sankar Dhar, Chitradeepa Chakroborty and Prashant Jha: "Goodness of Fit Based and Variable Selection in Non-parametric Measurement Error Model" in Statistical Modeling and Applications on Real-Time Problems, Editors: Chandra Shekhar and Raghaw Raman Sinha, Taylor's & Francis, CRC Press (Accepted for publication).

113. Swati Shukla, Subhra Sankar Dhar and Shalabh (2024): "Regression Modelling Under L_p-Norm Loss Function" in  Advances in Mathematics Research, Editor: Albert R. Baswell, Nova Science Publisher, pp. 121-144.

112.  Shalabh and Subhra Sankar Dhar (2023): "Testing the Goodness of Fit in Instrumental Variables Models" in Recent Advances in G Families of Probability Distributions, Editors: Mir Masoom Al, Irfan Ali, Haitham M. Youso and Mohamed Ibrahim, Taylor's & Francis, CRC Press (Accepted for publication).

111. Subhra Sankar Dhar and Shalabh (2022): "GIVE Statistic for Goodness of Fit in Instrumental Variables Models with Application to COVID Data''  Nature Scientific Reports (Nature  Publication), 12, 9472. DOI: https://doi.org/10.1038/s41598-022-13240-y. Download paper at https://rdcu.be/cPeT2)

110. Subhra Sankar Dhar, Udita Chatterjee and Shalabh (2022): "A Note on Asymptotic Distribution of Trimmed mean", Journal of the Indian Society for Probability and Statistics, (Special Issue of the 40th Convention of ISPS), 23, pp. 327-335, DOI: https://doi.org/10.1007/s41096-022-00136-3).

109. Shalabh (2022): "Statistical Linear Calibration in Data with Measurement Errors", in Recent Advances in Applied Statistics, Editors: David Hangel, Rao Shaheb Latpate, and Girish Chandra, Springer Nature,  pp. 291-307.

108. Sabara Parshad Rajeshbhai, Subhra Sankar Dhar, Shalabh (2022): "Fourth Wave of COVID-19 in India : Statistical Forecasting", https://doi.org/10.1101/2022.02.23.22271382,  https://www.medrxiv.org/content/10.1101/2022.02.23.22271382v1 Preprint manuscript uploaded at MedRxiv (Medical Arxive)  

107. Sabara Parshad Rajeshbhai, Subhra Sankar Dhar, Shalabh (2021): "Statistical Forecasting : Third Wave of COVID-19-With an Application to India", https://doi.org/10.1101/2021.12.20.21268150,  https://www.medrxiv.org/content/10.1101/2021.12.20.21268150v1 Preprint manuscript uploaded at MedRxiv (Medical Arxive)  

106. Shalabh and Subhra Sankar Dhar (2021): "Goodness of Fit in Non-parametric Regression Modelling'', Journal of Statistical Theory and Practice  (Invited paper for the special issue dedicated to Professor C.R. Rao on  "Celebrating the Centenary of Professor C R Rao") Journal of Statistical Theory and Practice volume 15, Article number: 18, https://doi.org/10.1007/s42519-020-00148-x

105. Shalabh, Subhra Sankar Dhar and N. Balakrishna (2021): "Goodness of Fit in Parametric and Non-parametric Econometric Models'' in Optimal Decision Making in Operations Research & Statistics: Methodologies and Applications, Editors: Leopoldo Eduardo Ca'rdenas-Barro'n, Aquil Ahmed, Irfan Ali and Ali Akbar Shaikh, pp. 68-91, Taylor's & Francis, Routledge, CRC Press. 

104. Anoop Chaturvedi, Shalabh and Sandeep Mishra (2021): "Generalized Bayes Estimator for Spatial Durbin Model'', Journal of Quantitative Economics (Special issue in honor of Late Professor A. L. Nagar,  19 (Suppl 1): S267-S285.

103. George Bresson, Anoop Chaturvedi, Mohammad Arshad Rahman and Shalabh (2021): "Seemingly Unrelated Regression with Measurement Error: Estimation via MCMC and Mean Field Variational Bayes Approximation", International Journal of Biostatistics, 17(1), pp. 75-97.

102. A.K.Md.E. Saleh and Shalabh (2020): "On Liu-Type Biased Estimators in Measurement Error Models", Statistics, Volume 54, No. 6, pp. 1171-1213.

101. Shalabh and Subhra Sankar Dhar (2020): "Statistical Modelling and Variable Selection in Climate Science", in Socio-economic and Eco-biological Dimensions of Climate Change: Strategies for Resource Use, Conservation and Ecological Sustainability, Editors: Niranjan Roy, Shubhadeep Roychoudhury, Sunil Nautiyal, Sunil K. Agarwal and Sangeeta Baksi, Springer, pp. 351-378.

100.  C.L. Cheng, Shalabh and Anoop Chaturvedi  (2019): "Goodness of Fit for Generalized Shrinkage Estimation", Theory of Probability and Mathematical Statistics (American Mathematical Society), No. 100,   pp. 177-197.

99. Shalabh and Jia-Ren Tsai (2017): "Ratio and Product Methods of Estimation of Population Mean in the Presence of Correlated Measurement Errors'', Communications in Statistics (Simulation and Computation), Vol. 46, No. 7, pp. 5566-5593.

98. Shalabh and C. Heumann (2017): "Use of Regression Method for Estimating Population Mean from Incomplete Survey Data through Imputation", Journal of Applied Statistical Science, Vol. 22, No. 3-4, pp. 407-427.

97.  Shalabh, Jia-Ren Tsai and Pen-Hwang Liau (2016):  "Immaculating the Inconsistent Estimator of Slope Parameter in Measurement Error Model with Replicated Data", Journal of  Statistical Computation and Simulation, Vol. 86,  Issue 17, pp. 3371-3387.

96.   C.L. Cheng, Shalabh and G. Garg (2016) : "Goodness of Fit in Restricted Measurement Error Models", Journal of Multivariate Analysis, 145, pp. 101-116.

95.  Anoop Chaturvedi and Shalabh (2014): "Bayesian Estimation of Regression Coefficients under Extended Balanced Loss Function", Communications in Statistics - Theory and Methods, Vol. 43, pp. 4253-4264.

94.  C.L. Cheng, Shalabh and G. Garg (2014): "Coefficient of Determination for Multiple Measurement Error Models", Journal of Multivariate Analysis,  123, pp. 137-152.   [This paper is in the category of ``Most Downloaded paper'' from JMVA in January 2014.]

93.  A.K.Md.E. Saleh and Shalabh (2014): "Ridge Regression Estimation Approach to Measurement Error Model", Journal of Multivariate Analysis, 123, pp. 68-84.  Extended version of the paper   [This paper is in the category of ``Most Downloaded paper'' from JMVA in January 2014]

       Corrigendum: Journal of Multivariate Analysis, 2014, 127, pp. 214.

92.  Shalabh (2013): "A revisit to the efficient forecasting in linear regression models'', Journal of Multivariate Analysis, 114, pp. 161-169.

91.  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.

90.  Sangita Kulathinal, Shalabh and Bijoy Joseph (2012): "Analysis of Pooled Time Series and Spatial Data with an Application to Water Level Data'', Journal of Applied Statistical Science, Vol. 18, No. 3, pp. 419-430.

89.  Shalabh and C. Heumann (2012): "Simultaneous Prediction of Actual and Average Values of Study variable Using Stein-rule Estimators" in Some Recent Developments in Statistical Theory and Application, (Editors: K. Kumar and  A. Chaturvedi), pp. 68-81, Brown Walker Press, U.S.A.

88.  Karthikeyan, G., J. Ramkumar and Shalabh (2012): "Performance Analysis of mu-ED-Milling Process Using Various Statistical Techniques'',  International Journal of Machining and Machinability of Materials, 123, pp. 183-203.

87.  M. Wissmann, H. Toutenburg and Shalabh (2011): "Role of Categorical Variables in Multicollinearity in Linear Regression Model", Journal of Applied Statistical Science, Volume 19, Issue 1, pp. 99-113.

86.  Gaurav Garg and Shalabh (2011): "Simultaneous Predictions under Exact Restrictions in Ultrastructural Model'', Journal of Statistical Research (in Special Volume on Measurement Error Models)  Vol. 45, No. 2, pp. 139-154.

85.  Shalabh, Gaurav Garg and Neeraj Misra (2011): Estimation of Regression Coefficients in a Restricted Measurement Error Model using  Instrumental Variables", Communications in Statistics (Theory & Methods), Vol. 40, pp. 3614-3629.

84.  Shalabh and C. Heumann (2011): "Simultaneous Prediction of Actual and Average Values of Study Variable Using Stein-rule Estimators", Technical Report No. 104, Department of Statistics, University of Munich, Munich, Germany.

83.  Shalabh, H. Toutenburg and A. Fieger (2010): "Using Diagnostic Measures to Detect Non-MCAR Processes in Linear Regression Models With Missing Covariates" Journal of Statistical Research, Vol. 44, No. 2, pp. 233-242 (Invited paper in honor of Professor Bradley Efron).

82.  Shalabh, Gaurav Garg and Neeraj Misra (2010): "Consistent Estimation of Regression Coefficients in Measurement Error Model Using Stochastic Apriori Information", Statistical Papers, Vol. 51, pp.717-748.

81.  A. Kukush, A. Malenko, H. Schneeweiss and Shalabh (2010): "Optimality of Quasi-Score in the Multivariate Mean-Variance Model with an Application to the Zero-Inflated Poisson Model with Measurement Errors", Statistics, Vol. 44, No. 4, pp. 381-396.

80.  Shalabh, H. Toutenburg and C. Heumann (2009): "Stein-Rule Estimation under an Extended Balanced Loss Function", Journal of Statistical Computation & Simulation, Vol. 79, No. 10, pp. 1259-1273.

79.  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.

78.  Shalabh, C.M. Paudel and N. Kumar (2009): "Consistent estimation of regression parameter under replicated ultrastructural model with non-normal errors",  Journal of Statistical Computation & Simulation,  Vol. 79, No. 3, pp. 251-274.

77.  Pen-Hwang Liau and Shalabh (2009): "Confidence Interval Estimation in Ultrastructural Model", Communications in Statistics (Theory & Methods), 38:5, pp. 675-681.

76.  H. Toutenburg, Shalabh and C. Heumann (2009): "Optimal Estimation in a Linear Regression Model Using Incomplete Prior Information'' in Statistical Inference, Econometric Analysis and Matrix Algebra (Springer) (Editors: Bernhard Schipp and Walter Kraemer), pp. 185-200.

75.  Shalabh, H. Toutenburg and C. Heumann (2008): "Mean Squared Error Matrix comparison of Least Squares and Stein-Rule Estimators for Regression Coefficients under Non-normal Disturbances", Metron, Vol. LXVI, No. 3, pp. 285-298.

74.  Gaurav Garg and Shalabh (2008): "Stein-rule Estimation in Ultrastructural Model Under Exact Linear Restrictions", Journal of Statistical Research ( Invited paper for the special issue in honor of Professor Mir Maswood Ali) Vol. 42, No. 2, pp. 159-180.

73.  C. Heumann and Shalabh (2008): "Weighted Mixed Regression Estimation Under Biased Stochastic Restrictions" in  Recent Advances In Linear Models and Related Areas (Springer) (Editors: Shalabh and C. Heumann), pp. 401-416.

72.  Toutenburg, H., V.K. Srivastava and Shalabh (2008): "Amputation versus imputation of missing values through ratio method in sample surveys", Statistical Papers, Vol. 49, No. 2, pp. 237-247.

71.  Shalabh, C.M. Paudel and N. Kumar (2008): "Simultaneous Prediction of Actual and Average Values of Response Variable in Replicated Measurement Error Models " in  Recent Advances In Linear Models and Related Areas (Springer) (Editors: Shalabh and C. Heumann), pp. 105-133.

70.  Toutenburg, H. and Shalabh (2008): "Improving the Estimation of Incomplete Regression Models through Pilot Investigations and Repeated Studies", Journal of Applied Statistical Science, Volume 16, No. 1, pp. 127-145.

69.  Shalabh and Alan Wan (2007): ``A Class of Estimators of  Regression Coefficient for Sign Change Problem in Measurement Error Models'',  Journal of Statistical Research, Vol. 41, No. 2, pp. 63-72.

68.  Shalabh, H. Toutenburg and C. Heumann (2007): "Risk Performance of Stein-Rule Estimators over the Least Squares Estimators of Regression Coefficients under Quadratic Loss Structures",  Journal of Statistical Studies ( Invited paper for the special issue in honor of 75th  birthday of Professor A.K.Md.E. Saleh) Vol. 26, pp. 97-103.

67.  Singh, H.P. and Shalabh (2007): "Estimation of population mean through estimated coefficient of variation", Journal of Applied Statistical Science, Volume 15, Issue 4, pp. 425-429.

66.  Shalabh, Gaurav Garg and Neeraj Misra (2007): "Restricted Regression Estimation in Measurement Error Models", Computational Statistics and Data Analysis 52, pp. 1149 -1166.

65.  H. Schneeweiss and Shalabh (2007): "On the Estimation of the Linear Relation when the Error Variances are known", Computational Statistics and Data Analysis, Vol. 52, pp. 1143 -1148.

64.  Shalabh, H. Toutenburg and C. Heumann (2007): "Stein-Rule Estimation under an Extended Balanced Loss Function", Technical Report No. 7, Department of Statistics, University of Munich, Munich, Germany.

63.  M. Wissmann, H. Toutenburg and Shalabh (2007): "Role of Categorical Variables in Multicollinearity in Linear Regression Model", Technical Report No. 8, Department of Statistics, University of Munich, Munich, Germany.

62.  C. Heumann and Shalabh (2007): "Weighted Mixed Regression Estimation Under Biased Stochastic Restrictions", Technical Report No. 10, Department of Statistics, University of Munich, Munich, Germany.

61.  Shalabh and Pen-Hwang Liau (2007): "Consistent Estimation of Regression Coefficient Through Weighted Arithmetic Mean of Inconsistent Estimators in Replicated Ultrastructural Model", Communications in Statistics (Theory and Methods), Volume 36, Issue 5, pp. 955-960.

60.  A. Kukush, A. Malenko, H. Schneeweiss and Shalabh (2007): "Optimality of Quasi-Score in the Multivariate Mean-Variance Model with an Application to the Zero-Inflated Poisson Model with Measurement Errors", Discussion paper 498, University of Munich, Munich, Germany. 

59.  Shalabh and H. Toutenburg (2006): "Consequence of Departure from Normality on the Properties of Calibration Estimators", Journal of Statistical Planning and Inference, Vol. 136, No. 12, pp. 4385-4396.

58.  Toutenburg, H., Shalabh and C. Heumann (2006) : "Use of Prior Information in the Form of Interval Constraints for Improved Estimation of Linear Regression Models with Some Missing Responses", Journal of Statistical Planning and Inference, Vol. 136, No. 8, pp. 2430-2445.

57.  Toutenburg, H., V.K. Srivastava and Shalabh (2006): "Estimation of Linear regression Models with Missingness of Observations on Both the Explanatory and Study Variables", Quality Technology and Quality Management, Vol. 3, No. 2, pp. 179-189.  

56.  Shalabh, H. Toutenburg and C. Heumann (2006): " Performance of Double k-class Estimators for Coefficients in Linear Regression Models with Non Spherical Disturbances under Asymmetric Losses", Discussion paper 509, University of Munich, Munich, Germany. 

55.  Shalabh, H. Toutenburg and C. Heumann (2006): " Mean squared error matrix comparison of least squares and Stein-rule estimators for regression coefficients under non-normal disturbances", Discussion paper 496, University of Munich, Munich, Germany. 

54.  Shalabh, H. Toutenburg and C. Heumann (2006): " Risk Performance Of Stein-Rule Estimators Over The Least Squares Estimators Of Regression Coefficients Under Quadratic Loss Structures", Discussion paper 495, University of Munich, Munich, Germany. 

53.  H. Schneeweiss and Shalabh (2006): " On the Estimation of the Linear Relation when the Error Variances are known", Discussion paper 493, University of Munich, Munich, Germany. 

52.  Toutenburg, H., V.K. Srivastava, Shalabh and C. Heumann (2005): "Estimation of Parameters in Multiple Regression With Missing Covariates using a Modified First Order Regression Procedure", Annals of Economics and Finance, 6, pp. 289-301.

51.  Toutenburg, H. and Shalabh (2005): "Estimation of Regression Coefficients subject to Exact Linear Restrictions when some observations are missing and Balanced Loss Function is used", TEST, Vol. 14, No. 2, pp. 385-396.

50.  Toutenburg, H. and Shalabh (2005): "Estimation of Linear Models with Missing Data: The Role of Stochastic Linear Constraints", Communications in Statistics - Theory and Methods Volume 34, 2, pp. 375-387.

49.  Shalabh and H. Toutenburg (2005): "On the regression method of estimation of population mean from incomplete survey data through imputation", Discussion paper 442, University of Munich, Munich, Germany.

48.  Shalabh and H. Toutenburg (2005): "Consequences of Departure from Normality on the Properties of Calibration Estimators", Discussion paper 441, University of Munich, Munich, Germany. 

47.  Shalabh, Leon J. Gleser and Ori Rosen (2004): "On the Usefulness of Knowledge of Error Variances in the Consistent Estimation of an Unreplicated Ultrastructural Model", Journal of Statistical Computation & Simulation, 74, 6, pp. 391-417.

46.  Chaturvedi, A. and Shalabh (2004): "Risk and Pitman Closeness Properties of Feasible Generalized Double k-class estimators in Linear Regression Models with Non-spherical Disturbances under Balanced Loss Function", Journal of Multivariate Analysis, 90, 229-256.

45.  Schaffrin, B., H. Toutenburg and Shalabh (2003): "On the Impact of Missing Values on the Reliability Measures in a Linear Model", Journal of Statistical Research, (Invited paper for Special Volume in Honor of Professor A.K.Md.E. Saleh) , 37, 2, pp. 251-260.

44.  Shalabh (2003): "Consistent Estimation of Coefficients in Measurement Error Models with Replicated Observations", Journal of Multivariate Analysis, Vol. 86, No. 2, pp. 227-241.  

43.  Toutenburg, H. and Shalabh (2003): "Estimation of Regression Models with Equi-correlated Responses when Some Observations on Response Variable are Missing", Statistical Papers, Vol. 44, No. 10, pp. 217-232.

42.  Toutenburg, H. and Shalabh (2003) : "Pseudo Minimax Linear and Mixed Regression Estimation of Regression Coefficients when Prior Estimates are available", Statistics and Probability Letters, 63, pp. 35-39.

41.  Shalabh and R. Chandra (2002): "Prediction in Restricted Regression Models", Journal of Combinatorics, Information System and Sciences, Vol. 29, Nos. 1-4, pp. 229-238.

40.  Toutenburg, H. and Shalabh (2002) : "Prediction of Response Values in Linear Regression Models from Replicated Experiments", Statistical Papers, 43, pp. 423-433.

39.  Shalabh (2002) : "Effects of a Trended Regressor on the Efficiency Properties of the Least Squares and Stein-rule Estimation of Regression Coefficients", Handbook of Applied Econometrics and Statistical Inference, Editors: A. Ullah, A. Wan and A. Chaturvedi, Marcell Dekker, pp. 327-346.

38.  Shalabh (2001) : "Pitman Closeness Comparison of Least Squares and Stein-rule Estimators in Linear Regression Models with Non-normal Disturbances", The American Journal of Mathematical and Management Sciences (AJMMS), Vol. 21, No. 1 , pp. 89-100.  

37.  Shalabh (2001): "Least Squares Estimators in Measurement Error Model under the Balanced Loss Function", TEST, Vol. 10, 2, 301-308.

36.  Toutenburg, H. and Shalabh (2001) : "Synthesizing the Classical and Inverse Methods in Linear Calibration", SFB Discussion Paper 252, University of Munich, Munich, Germany.

35.  Shalabh (2001) : "Estimation of Bias and Standard Error of An Improved Estimator of Normal Mean", Metrika, 54, 43-51.

34.  Srivastava, A.,K. and Shalabh (2001): "Effect of Measurement Errors On the Regression Method of Estimation in Survey Sampling", Journal of Statistical Research, Vol. 35, No. 2 , pp. 35-44.

33.  Toutenburg, H. and Shalabh (2001): "Use of Prior Information in the form of interval constraints for the Improved Estimation of Linear Regression Models with some Missing Responses", SFB Discussion Paper 240, University of Munich, Munich, Germany.

32.  Ullah, A., Shalabh and D. Mukherjee (2001): "Consistent Estimation of Regression Coefficients in Replicated data with non-normal Measurement Errors", Annals of Economics and Finance, 2, 249-264.

31.  Toutenburg, H. and Shalabh (2001) : "Estimation of Linear Models with Missing Data: The role of Stochastic Linear Constraints", SFB Discussion Paper 239, University of Munich, Munich, Germany.

30.  Toutenburg, H. and Shalabh (2001) : "A note on the comparison of minimax linear and mixed regression estimation of regression coefficients when prior estimates are available", SFB Discussion Paper 238, University of Munich, Munich, Germany.

29.  Shalabh (2001): "Consistent Estimation through Weighted Harmonic Mean of Inconsistent Estimators in Replicated Measurement Error Models", Econometric Reviews, Vol. 20, 4, 507-510.

28.  Toutenburg, H. and Shalabh (2001) : "Use of Minimum Risk Approach in the Estimation of Regression Models with Missing Observations", Metrika, 54, 247-249.

27.  Srivastava A.K. and Shalabh (2000) : "On the Choice of Direction for Minimization of Residuals in Ultrastructural Model", Statistica, annoLX, n.1, 97-107.  

26.  Shalabh and A.T.K. Wan (2000) : "Stein-rule Estimation in Mixed Regression Models", Biometrical Journal , Vol 42, pp.203-214.  

25.  Shalabh (2000): "Note on a Family of Unbiased Predictors for the Equi-correlated Responses in Linear Regression Models", Statistical Papers, Vol. 41, 2, pp. 237-241.

24.  Shalabh (2000): "Prediction of Values of Variables in Linear Measurement Error Model", Journal of Applied Statistics, 27, 4, 475-482.  

23.  Toutenburg, H. and Shalabh (2000): "Improved Prediction in Linear Regression Model with Stochastic Linear Constraints", Biometrical Journal, 42, 1, 71-86.

22.  Toutenburg, H. and Shalabh (1999) : "Estimation of Regression Models with Equi-correlated Responses when some Observations on the Response Variable are Missing", SFB Discussion Paper 174, University of Munich, Munich, Germany.

21.  Toutenburg, H. and Shalabh (1999) : "Estimation of Regression Coefficients Subject to Exact Linear Restrictions when some Observations are Missing and Balanced Loss Function is Used", SFB Discussion Paper 163, University of Munich, Munich, Germany.

20.  Toutenburg, H. and Shalabh (1999) : "Improving the Estimation of Incomplete Regression Models through Pilot Investigations and Repeated Studies", SFB Discussion Paper 154, University of Munich, Munich, Germany.

19.  Shalabh (1999): "Improving the Predictions in Linear Regression Models", Journal of Statistical Research, Vol. 33, No. 1.

18.  Toutenburg, H. and Shalabh (1998) : "Improved Predictions in Linear Regression Models with Stochastic Linear Constraints", SFB Discussion Paper 124, University of Munich, Munich, Germany.

17.  Toutenburg, H. and Shalabh (1998) : "Use of minimum risk approach in the estimation of regression models with missing observation", SFB Discussion Paper 118, University of Munich, Munich, Germany.

16.  Toutenburg, H. and Shalabh (1998) : "Prediction of Response Values in Linear Regression Models from Replicated Experiments", SFB Discussion Paper 112, University of Munich, Munich, Germany.

15.  Shalabh (1998): "Improved Estimation in Measurement Error Models Through Stein-rule Procedure", Journal of Multivariate Analysis, 67, 35-48. , Corrigendum : Journal of Multivariate Analysis, 74, p. 162, (2000).

14.  Shalabh (1998): "Unbiased Prediction in Linear Regression Model with Equicorrelated Responses", Statistical Papers, Vol. 39, No. 2, pp.237-244.

13.  Srivastava, A.K. and Shalabh (1997): "Asymptotic Efficiency Properties of Least Squares Estimation in Ultrastructural Model", TEST, Vol. 6, No. 2, pp. 419-431.

12.  Srivastava, A.K. and Shalabh (1997): "Consistent Estimation for the Non-normal Ultrastructural Model", Statistics and Probability Letters, 34, pp. 67-73.

11.  Shalabh (1997): "On Efficient Forecasting in Linear Regression Models", Journal of Quantitative Economics, Vol. 36, No. 2, pp. 133-140.

10.  Srivastava, A.K. and Shalabh (1997): "Improved Estimation of Slope Parameter in a Linear Ultrastructural Model when Measurement Errors are not Necessarily Normal", Journal of Econometrics, 78, pp. 153-157.

9.      Shalabh (1997): "Ratio Method of Estimation in the Presence of Measurement Errors", Indian Journal of Agricultural Statistics, Vol. 50, No.2, pp. 150-155.

8.      Srivastava, A.K. and Shalabh (1997): "A New Property of Stein Procedure in Measurement Error Model", Statistics and Probability Letters, 32, pp. 231-234.

7.      Toutenburg, H. and Shalabh (1996): "Predictive Performance of the Methods of Restricted and Mixed Regression Estimators", Biometrical Journal, 38, 8, pp. 951-959.

6.      Srivastava, A.K. and Shalabh (1996): "A Composite Target Function for Prediction in Economic Models", Indian Journal of Applied Economics, Vol. 5, No. 5, pp. 251-257.

5.      Srivastava, A.K. and Shalabh (1996): "Efficiency Properties of Least Squares and Stein-Rule Predictions in Linear Regression Model", Journal of Applied Statistical Science, Vol. 4, No. 2/3, pp. 141-145.

4.      Srivastava, A.K. and Shalabh (1996): "Properties of a Consistent Estimation Procedure in Ultrastructural Model when Reliability Ratio is Known", Microelectronics and Reliability, Vol. 36, No. 9, pp. 1249-1252.

3.      Rao, B. and Shalabh (1995): "Unit Roots, Cointegration and the Demand for Money in India", Applied Economic Letters, 2, 397-399.  

2.      Shalabh (1995): "Performance of Stein - rule Procedure for Simultaneous Prediction of Actual and Average Values of Study Variable in Linear Regression Model", Bulletin of the International Statistical Institute, The Netherlands, pp. 1375-1390.

1.      Srivastava, A.K. and Shalabh (1995): "Predictions in Linear Regression Models With Measurement Errors", Indian Journal of Applied Economics, Vol. 4, No. 2, pp. 1-14.