Shalabh
shalab@iitk.ac.in
shalabh1@yahoo.com
Department of Mathematics & Statistics
Indian
Books
1. Title: Linear Models and
Generalizations  Least Squares and Alternatives 

2. Title: Recent Advances In Linear
Models and Related Areas 

3. Title: Statistical Analysis of
Designed Experiments 

4. Title: Introduction to Statistics and Data Analysis
 With Exercises, Solutions and Applications in R 
Research
Papers
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. 114.
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
3.
Rao, B. and Shalabh (1995): "Unit Roots,
Cointegration and the Demand for Money in
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. 12491252.
5.
Srivastava, A.K. and Shalabh (1996): "Efficiency
Properties of Least Squares and SteinRule Predictions in Linear Regression
Model", Journal of Applied Statistical Science, Vol. 4, No. 2/3,
pp. 141145.
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. 251257.
7.
Toutenburg, H. and Shalabh (1996): "Predictive
Performance of the Methods of Restricted and Mixed Regression Estimators",
Biometrical Journal, 38, 8, pp. 951959.
8.
Srivastava, A.K. and Shalabh (1997): "A New
Property of Stein Procedure in Measurement Error Model", Statistics and
Probability Letters, 32, pp. 231234.
9.
Shalabh (1997): "Ratio Method of Estimation in
the Presence of Measurement Errors", Indian Journal of Agricultural
Statistics, Vol. 50, No.2, pp. 150155.
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. 153157.
11. Shalabh (1997): "On Efficient Forecasting in Linear Regression Models", Journal of Quantitative Economics, Vol. 36, No. 2, pp. 133140.
12.
Srivastava, A.K. and Shalabh (1997): "Consistent
Estimation for the Nonnormal Ultrastructural Model", Statistics and
Probability Letters, 34, pp. 6773.
13.
Srivastava, A.K. and Shalabh (1997): "Asymptotic
Efficiency Properties of Least Squares Estimation in Ultrastructural
Model", TEST, Vol. 6, No. 2, pp. 419431.
14.
Shalabh (1998): "Unbiased Prediction in Linear
Regression Model with Equicorrelated Responses", Statistical Papers,
Vol. 39, No. 2, pp.237244.
15. Shalabh (1998): "Improved Estimation in Measurement Error Models Through Steinrule Procedure", Journal of Multivariate Analysis, 67, 3548. , Corrigendum : Journal of Multivariate Analysis, 74, p. 162, (2000).
16.
Toutenburg,
H. and Shalabh (1998) : "Prediction of Response Values in Linear
Regression Models from Replicated Experiments", SFB Discussion Paper
112,
17.
Toutenburg,
H. and Shalabh (1998) : "Use of minimum risk approach in the estimation of
regression models with missing observation", SFB Discussion Paper 118,
18.
Toutenburg,
H. and Shalabh (1998) : "Improved Predictions in Linear Regression Models
with Stochastic Linear Constraints", SFB Discussion Paper 124,
19. Shalabh (1999): "Improving the Predictions in Linear Regression Models", Journal of Statistical Research, Vol. 33, No. 1.
20.
Toutenburg,
H. and Shalabh (1999) : "Improving the Estimation of Incomplete Regression
Models through Pilot Investigations and Repeated Studies", SFB
Discussion Paper 154,
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,
22.
Toutenburg,
H. and Shalabh (1999) : "Estimation of Regression Models with
Equicorrelated Responses when some Observations on the Response Variable are
Missing", SFB Discussion Paper 174,
23. Toutenburg, H. and Shalabh (2000): "Improved Prediction in Linear Regression Model with Stochastic Linear Constraints", Biometrical Journal, 42, 1, 7186.
24. Shalabh (2000): "Prediction of Values of Variables in Linear Measurement Error Model", Journal of Applied Statistics, 27, 4, 475482.
25. Shalabh (2000): "Note on a Family of Unbiased Predictors for the Equicorrelated Responses in Linear Regression Models", Statistical Papers, Vol. 41, 2, pp. 237241.
26. Shalabh and A.T.K. Wan (2000) : "Steinrule Estimation in Mixed Regression Models", Biometrical Journal , Vol 42, pp.203214.
27. Srivastava A.K. and Shalabh (2000) : "On the Choice of Direction for Minimization of Residuals in Ultrastructural Model", Statistica, annoLX, n.1, 97107.
28. Toutenburg, H. and Shalabh (2001) : "Use of Minimum Risk Approach in the Estimation of Regression Models with Missing Observations", Metrika, 54, 247249.
29. Shalabh (2001): "Consistent Estimation through Weighted Harmonic Mean of Inconsistent Estimators in Replicated Measurement Error Models", Econometric Reviews, Vol. 20, 4, 507510.
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,
31.
Toutenburg,
H. and Shalabh (2001) : "Estimation of Linear Models with Missing Data: The
role of Stochastic Linear Constraints", SFB Discussion Paper 239,
32. Ullah, A., Shalabh and D. Mukherjee (2001): "Consistent Estimation of Regression Coefficients in Replicated data with nonnormal Measurement Errors", Annals of Economics and Finance, 2, 249264.
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,
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. 3544.
35.
Shalabh
(2001) : "Estimation of Bias and Standard Error of An Improved Estimator
of
36.
Toutenburg,
H. and Shalabh (2001) : "Synthesizing the Classical and Inverse Methods in
Linear Calibration", SFB Discussion Paper 252,
37. Shalabh (2001): "Least Squares Estimators in Measurement Error Model under the Balanced Loss Function", TEST, Vol. 10, 2, 301308.
38. Shalabh (2001) : "Pitman Closeness Comparison of Least Squares and Steinrule Estimators in Linear Regression Models with Nonnormal Disturbances", The American Journal of Mathematical and Management Sciences (AJMMS), Vol. 21, No. 1 , pp. 89100.
39. Shalabh (2002) : "Effects of a Trended Regressor on the Efficiency Properties of the Least Squares and Steinrule Estimation of Regression Coefficients", Handbook of Applied Econometrics and Statistical Inference, Editors: A. Ullah, A. Wan and A. Chaturvedi, Marcell Dekker, pp. 327346.
40. Toutenburg, H. and Shalabh (2002) : "Prediction of Response Values in Linear Regression Models from Replicated Experiments", Statistical Papers, 43, pp. 423433.
41. Shalabh and R. Chandra (2002): "Prediction in Restricted Regression Models", Journal of Combinatorics, Information System and Sciences, Vol. 29, Nos. 14, pp. 229238.
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. 3539.
43. Toutenburg, H. and Shalabh (2003): "Estimation of Regression Models with Equicorrelated Responses when Some Observations on Response Variable are Missing", Statistical Papers, Vol. 44, No. 10, pp. 217232.
44. Shalabh (2003): "Consistent Estimation of Coefficients in Measurement Error Models with Replicated Observations", Journal of Multivariate Analysis, Vol. 86, No. 2, pp. 227241.
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. 251260.
46. Chaturvedi, A. and Shalabh (2004): "Risk and Pitman Closeness Properties of Feasible Generalized Double kclass estimators in Linear Regression Models with Nonspherical Disturbances under Balanced Loss Function", Journal of Multivariate Analysis, 90, 229256.
47.
48.
Shalabh
and H. Toutenburg (2005): "Consequences of Departure from Normality on the
Properties of Calibration Estimators", Discussion paper 441,
49.
Shalabh
and H. Toutenburg (2005): "On the regression method of estimation of
population mean from incomplete survey data through imputation",
Discussion paper 442,
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. 375387.
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. 385396.
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. 289301.
53.
H.
Schneeweiss and Shalabh (2006): " On the Estimation of the Linear Relation
when the Error Variances are known", Discussion paper 493,
54.
Shalabh,
H. Toutenburg and C. Heumann (2006): "
Risk Performance Of SteinRule
Estimators Over The Least Squares Estimators Of Regression Coefficients Under
Quadratic Loss Structures", Discussion paper 495,
55.
Shalabh,
H. Toutenburg and C. Heumann (2006): " Mean squared error matrix
comparison of least squares and Steinrule estimators for regression
coefficients under nonnormal disturbances", Discussion paper 496,
56.
Shalabh,
H. Toutenburg and C. Heumann (2006): " Performance of Double kclass
Estimators for Coefficients in Linear Regression Models with Non Spherical
Disturbances under Asymmetric Losses", Discussion paper 509,
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. 179189.
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. 24302445.
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. 43854396.
60.
A.
Kukush, A. Malenko, H. Schneeweiss and Shalabh (2007): "Optimality of
QuasiScore in the Multivariate MeanVariance Model with an Application to the
ZeroInflated Poisson Model with Measurement Errors", Discussion paper
498,
61. Shalabh and PenHwang 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. 955960.
62.
C.
Heumann and Shalabh (2007): "Weighted Mixed Regression Estimation Under
Biased Stochastic Restrictions", Technical Report No. 10, Department of
Statistics,
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,
64.
Shalabh,
H. Toutenburg and C. Heumann (2007): "SteinRule Estimation under an
Extended Balanced Loss Function", Technical Report No. 7, Department of
Statistics,
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.
66. Shalabh, Gaurav Garg and Neeraj Misra (2007): "Restricted Regression Estimation in Measurement Error Models", Computational Statistics and Data Analysis 52, pp. 1149 1166.
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. 425429.
68. Shalabh, H. Toutenburg and C. Heumann (2007): "Risk Performance of SteinRule 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. 97103.
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. 6372.
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. 127145.
71.
Shalabh,
C.M. Paudel and
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. 237247.
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. 401416.
74. Gaurav Garg and Shalabh (2008): "Steinrule 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. 159180.
75. Shalabh, H. Toutenburg and C. Heumann (2008): "Mean Squared Error Matrix comparison of Least Squares and SteinRule Estimators for Regression Coefficients under Nonnormal Disturbances", Metron, Vol. LXVI, No. 3, pp. 285298.
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. 185200.
77. PenHwang Liau and Shalabh (2009): "Confidence Interval Estimation in Ultrastructural Model", Communications in Statistics (Theory & Methods), 38:5, pp. 675681.
78. Shalabh, C.M. Paudel and N. Kumar (2009): "Consistent estimation of regression parameter under replicated ultrastructural model with nonnormal errors", Journal of Statistical Computation & Simulation, Vol. 79, No. 3, pp. 251274.
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. 14981520.
80. Shalabh, H. Toutenburg and C. Heumann (2009): "SteinRule Estimation under an Extended Balanced Loss Function", Journal of Statistical Computation & Simulation, Vol. 79, No. 10, pp. 12591273.
81. A. Kukush, A. Malenko, H. Schneeweiss and Shalabh (2010): "Optimality of QuasiScore in the Multivariate MeanVariance Model with an Application to the ZeroInflated Poisson Model with Measurement Errors", Statistics, Vol. 44, No. 4, pp. 381396.
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.717748.
83. Shalabh, H. Toutenburg and A. Fieger (2010): "Using Diagnostic Measures to Detect NonMCAR Processes in Linear Regression Models With Missing Covariates" Journal of Statistical Research, Vol. 44, No. 2, pp. 233242 (Invited paper in honor of Professor Bradley Efron).
84. Shalabh and C. Heumann (2011): "Simultaneous Prediction of Actual and Average Values of Study Variable Using Steinrule Estimators", Technical Report No. 104, Department of Statistics, University of Munich, Munich, Germany.
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. 36143629.
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. 139154.
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. 99113.
88. Karthikeyan,
G., J. Ramkumar and Shalabh (2012): "Performance Analysis of
muEDMilling
Process Using Various Statistical Techniques'', International Journal
of Machining and Machinability of Materials, 123, pp. 183203.
89. Shalabh and C. Heumann (2012): "Simultaneous Prediction of Actual and Average Values of Study variable Using Steinrule Estimators" in Some Recent Developments in Statistical Theory and Application, (Editors: K. Kumar and A. Chaturvedi), pp. 6881, Brown Walker Press, U.S.A.
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. 419430.
91. Shalabh, G. Garg and C. Heumann (2012): "Performance of Double kclass Estimators for Coefficients in Linear Regression Models with Non Spherical Disturbances under Asymmetric Losses'', Journal of Multivariate Analysis, 112, pp. 3547.
92. Shalabh (2013): "A revisit to the efficient forecasting in linear regression models'', Journal of Multivariate Analysis, 114, pp. 161169.
93. A.K.Md.E. Saleh and Shalabh (2014): "Ridge Regression Estimation Approach to Measurement Error Model", Journal of Multivariate Analysis, 123, pp. 6884. 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.
94. C.L. Cheng, Shalabh and G. Garg (2014): "Coefficient of Determination for Multiple Measurement Error Models", Journal of Multivariate Analysis, 123, pp. 137152. [This paper is in the category of ``Most Downloaded paper'' from JMVA in January 2014.]
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. 42534264.
96. C.L. Cheng, Shalabh and G. Garg (2016) : "Goodness of Fit in Restricted Measurement Error Models", Journal of Multivariate Analysis, 145, pp. 101116.
97. 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. 34, pp. 407427.
98. Shalabh and JiaRen 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. 55665593.
99. Shalabh, JiaRen Tsai and PenHwang Liau (2016): "Immaculating the Inconsistent Estimator of Slope Parameter in Measurement Error Model with Replicated Data", Journal of Statistical Computation and Simulation, (In press).
1. G. Karthikeyan, J. Ramkumar and Shalabh (2009): ``Estimation of Diameter Machining of Tungsten Electrode by Micro Block EDG Process'', Proceedings of IPRoMM 2009 (National Conference on Design and Manufacturing Issues in Automotive and Allied Industries), 1011 July 2009, Chennai, India, Eds. R. Gnanamoorthy, M. Kamraj and M. Sreekumar.
2. Shalabh and G. Garg (2013): ``Coefficient of Determination for Multiple Measurement Error Models'', Proceedings of the 59th ISI (International Statistical Institute) World Statistics Congress, 2530 August 2013, Hong Kong (Session STS044).