Some Improved Mixed Regression Estimators and their Comparison when Disturbance Terms follow Multivariate T-Distribution

Authors

  • Manoj Kumar Department of Statistics, Panjab University, Chandigarh, India
  • Vikas Bist Department of Mathematics, Panjab University, Chandigarh, India
  • Man Inder Kumar Department of Statistics, Panjab University, Chandigarh, India

DOI:

https://doi.org/10.23755/rm.v32i0.330

Keywords:

Stochastic restrictions, Mixed regression estimator, Stein- rule estimator, Multivariate t-distribution

Abstract

The Mean square error matrices, bias vector and risk functions of proposed improved mixed regression estimators are obtained by employing the small disturbance approximation technique under the condition, when disturbance terms follows multivariate t-distribution. Further, the risk function criterion is used to examine the efficiency of proposed improved mixed regression estimators.

Author Biography

  • Man Inder Kumar, Department of Statistics, Panjab University, Chandigarh, India

    PhD Student,

    Department of Statistics,

    Panjab University,

    Chandigarh, India

References

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Published

2017-07-30

Issue

Vol. 32 (2017)

Section

Volume 32-2017

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