International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2018, Vol. 3, Issue 2, Part G

Inference in linear model with stochastic prior information constraints and compatibility tests


Author(s): Dr. AK Nagaraju, P Sri Vyshnavi, C Mani, Dr. K Sreenivasulu, H Ravi Shankar, C Narayana and P Balasiddamuni

Abstract: In the estimation of linear statistical model, generally the information contained in the sample observations on dependent variable may be used. In the applied econometric work, additional information namely prior information about unknown regression coefficients or the unknown error variance may be available for the estimation process. In this situation, the econometrician uses both the sample and other prior information on parameters in the estimation and testing. In this paper a new estimation method has been derived for linear regression model under stochastic prior information restrictions. A compatibility test statistic prior information on parameters of linear regression model.

Pages: 549-556 | Views: 402 | Downloads: 3

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How to cite this article:
Dr. AK Nagaraju, P Sri Vyshnavi, C Mani, Dr. K Sreenivasulu, H Ravi Shankar, C Narayana and P Balasiddamuni. Inference in linear model with stochastic prior information constraints and compatibility tests. International Journal of Statistics and Applied Mathematics. 2018; 3(2): 549-556.
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International Journal of Statistics and Applied Mathematics