Applied Regression Analysis

Paper Code: 
STT 144(A)
Credits: 
4
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 

The students would be exposed to the concepts of regression modelling. Emphasis will be laid on applying model and regression theory for data analysis. 

12.00
Unit I: 
Unit I

Residuals and their analysis, Influential observations, Power transformation for dependent and independent variables.

 

12.00
Unit II: 
Unit II

Robust and L-1 regression, estimation of prediction error by cross-validation and boot-strap, non-linear regression models.

 

12.00
Unit III: 
Unit III

Different methods of estimation (Least squares, Maximum Likelihood), Asymptotic properties of estimators. Generalized linear models.

 

12.00
Unit IV: 
Unit IV

Analysis of binary and grouped data by using logistic models. Log-linear models. Random and mixed effect models.

 

12.00
Unit V: 
Unit V

Maximum likelihood, MINQUE and restricted maximum likelihood estimators of variance components, Best linear unbiased predictors (BLUP), Growth curves.

 

Essential Readings: 

Books Recommended/References:

 

  • Bates, D.M. and Watts, D.G.(1988). Nonlinear Regression Analysis and its application, Wiley, New York.
  • Cook, R.D. and Weisberg, S(1992). Residuals and inference in Regression , Chapman and Hall, London.
  • Draper, N. R. and Smith, H.(1988). Applied Regression Analysis, 3rd ed., Wiley New yark.
  • Efron,B.and Tibsirani,J.R.(1993). An Introduction to the Bootstrap, Chapman and Hal, New York.
  • Kshirsagar, A.M. (1995). Growth Curves, Marcel and Dekker, New York.
  • MoCullagh, P. and Nelder, J.A. (1989), Generalized Linear Models, 2 nd Chapman and Hall, London. . 7. Searle, S.R. (1987). Linear Models for Unbalanced data, Wiley, New York
  • Seber, G.A. and Wild, G.J.(1989)Nonlinear regression. Wiley, New York.
  • Rao, C.R. (1973): Linear Statistical Inference and its Applications, Wiley Fastern

 

Academic Year: 
2020-2021
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