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Restricted linear models and their applications

S.G. Parekh1 , S.R. Patel2

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.2 , pp.267-271, Apr-2019


CrossRef-DOI:   https://doi.org/10.26438/ijsrmss/v6i2.267271


Online published on Apr 30, 2019


Copyright © S.G. Parekh, S.R. Patel . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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IEEE Style Citation: S.G. Parekh, S.R. Patel, “Restricted linear models and their applications,” International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.6, Issue.2, pp.267-271, 2019.

MLA Style Citation: S.G. Parekh, S.R. Patel "Restricted linear models and their applications." International Journal of Scientific Research in Mathematical and Statistical Sciences 6.2 (2019): 267-271.

APA Style Citation: S.G. Parekh, S.R. Patel, (2019). Restricted linear models and their applications. International Journal of Scientific Research in Mathematical and Statistical Sciences, 6(2), 267-271.

BibTex Style Citation:
@article{Parekh_2019,
author = {S.G. Parekh, S.R. Patel},
title = {Restricted linear models and their applications},
journal = {International Journal of Scientific Research in Mathematical and Statistical Sciences},
issue_date = {4 2019},
volume = {6},
Issue = {2},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {267-271},
url = {https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=1244},
doi = {https://doi.org/10.26438/ijcse/v6i2.267271}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i2.267271}
UR - https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=1244
TI - Restricted linear models and their applications
T2 - International Journal of Scientific Research in Mathematical and Statistical Sciences
AU - S.G. Parekh, S.R. Patel
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 267-271
IS - 2
VL - 6
SN - 2347-2693
ER -

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Abstract :
In this paper we have considered the usual Gauss-Marcoff model with some restrictions on parameters. Usually Gauss-Marcoff model has been discussed by many authors. Further some of the applications have been applied to the real life data on kidney infection. Unified theory for both types of models has been developed.

Key-Words / Index Term :
Linear models; Gauss-Markov model; Unified theory; kidney infection

References :
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[2] John P. Hoffmann,“Generalized linear models and Applied Aproach”, 2004.
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[4] Rao, C. R., “Estimation in linear models with mixed effects: A Unified theory”. Prac. Second international tam pore conference in Statistics, ed., T.pukkila and S. Puntanen, pp. 79-98, 1988
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[6] Miller SJ. “The method of least squares”, Mathematics Department brown University, pp.1-7, 2006.
[7] Cankaya S, Kayaalp GT, Sangum L, Tahtali Y, Akar M., “A Comparative study study of estimation methods for parameters in multiple linear regression model”, J.Appl Anim Res,Vol. 29, Issue.1, pp.43-47, 2006.
[8] Cankaya S, “A Comparative study study of some estimation methods for parameters and effects of outliers in simple regression model for research on small ruminants”, Trop Anim Health Pro, Vol.41, Issue.1, pp.35-41, 2009.
[9] Cankaya S, Eker S, Tahtali Y, Ceyhan A., “Comparison of some estimation methods for parameters of simple regression model in the presence of outliers,” 7th National Animal Science Congress, Adana, Turkey, pp.136-141, 14-16 September, 2011.
[10] Alvin C. Rencher “Linear models in Statistics”, John Wiley & Sons, 2000.
[11] McGilchrist, C.A., Aisbett, C.W., “Regression with frailty in survival analysis,” Biometrics, Vol. 47, pp.461 – 466, 1991.

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