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145-156

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- Master Program in Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia

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- Department of Mathematics, Faculty of Science and Technology, Universitas Islam Negeri Sunan Gunung Djati Bandung, Indonesia

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- Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Indonesia

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- Department of Marine Science, Faculty of Fishery and Marine Science, Universitas Padjadjaran, Indonesia

References

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- [2] Bappenas, Directorate of Sectoral Development Performance Evaluation of Ministry of VAT, Changes in Productivity of Indonesia's Manufacturing Industry and Its Affecting Factors: Panel Data Analysis 2004-2009. Bappenas Annual Report (2010)
- [3] CW Cobb, PH Douglas, A Theory of Production. American Economic Review (1928) 139-165
- [4] Dan Anbar, A stochastic Newton-Raphson method. Journal of Statistical Planning and Inference (1978) 153-163
- [5] E. Khater, A Cobb – Douglas Function Based Index for Human Development in Egypt. International Journal Contemporer Math Science (2012) 591-598
- [6] Gabriel Eduard Vîlcu, A geometric perspective on the generalized Cobb–Douglas production functions. Applied Mathematics Letters 24 (2011) 777–783
- [7] H.T. Banks, Michele L. Joyner. AIC under the framework of least squares estimation. Applied Mathematics Letters 74 (2017) 33-45
- [8] J. Morio, M. Balesdent, Estimation of Rare Event Probabilities in Complex Aerospace and Other Systems: Introduction to rare event probability estimation. Woodhead Publishing (2015) 1-2
- [9] J.H Tressler, C.Fmenezes, Constant returns to scale and competitive equilibrium under uncertainty. Journal of Economic Theory (1983) 383-391
- [10] J.H. Proost, Combined proportional and additive residual error models in population pharmacokinetic modelling. European Journal of Pharmaceutical Sciences (2017) S78-S82
- [11] James E.Rauch, Increasing returns to scale and the pattern of trade. Journal of International Economics 26 (1989) 359-369
- [12] Judge, George G., et al, The Theory and Practice of Econometrics. Wiley (1980)
- [13] K.J.Friston, et al, Classical and Bayesian Inference in Neuroimaging: Theory. Neuro Image 16 (2002) 465–483
- [14] K.I. Kim, et al, Estimating Production Functions with Control Functions When Capital is Measured with Error. Journal of Econometrics (2016) 267-279
- [15] Li Li, Yujin Hu, Xuelin Wang, Design sensitivity and Hessian Matrix of Generalized Eigenproblems. Mechanical Systems and Signal Processing 43 (2014) 272–294
- [16] Lin B, Philip A, Inter-fuel substitution possibilities in South Africa: A translog production function approach. Energy (2017) 822-831
- [17] LIU Anguo, GAO Ge, Yang Kaizhong, Returns to scale in the production of selected manufacturing sectors in China. Energy Procedia 5 (2011) 604–612
- [18] M. Fosgerau, M. Bierlaire, Discrete choice models with multiplicative error terms. Transportation Research Part B: Methodological (2009) 494-505
- [19] M. Hossain, A. Kumar Majumder, T. Basak, An Application of Non-Linear Cobb-Douglas Production Function to Selected Manufacturing Industries in Bangladesh. Open Journal of Statistics (2012) 460-468
- [20] Madhumita Pal, M. Seetharama Bhat, Least Square Estimation of Spacecraft Attitude along with Star Camera Parameters. IFAC Proceedings Volumes (2014) 20-25
- [21] N. Tsirivas, A generalization of universal Taylor series in simply connected domains. Journal of Mathematical Analysis and Applications 388 (2012) 361–369
- [22] Nicholson W, Snyder C.M., Intermediate Microeconomics and Its Application. 11th Edition. Mason, Ohio: South-Western/Cengage Learning, c2010.
- [23] Pingge Chen, Yuejian Peng , Suijie Wang, The Hessian matrix of Lagrange function. Linear Algebra and its Applications 531 (2017) 537–546
- [24] R. Rogerson, J. Wallenius, Retirement, home production and labor supply elasticities. Journal of Monetary Economics 78 (2016) 23–34
- [25] Rajiv D.Banker, R.M.Thrall, Estimation of returns to scale using data envelopment analysis. European Journal of Operational Research 62 (1992) 74-84
- [26] Raymon P. Canale, Steven C. Chapra, Raymon P. Canale, Steven C. Chapra, Numerical Methods for Engineers. McGraw-Hill Fourth Edition (2002)
- [27] Spyros G. Makridakis, Steven C. Wheelwright, Rob J. Hyndman, Forecasting: Methods and Applications, 3rd Edition (1998)
- [28] Stephen M. Stigler, Gauss and the Invention of Least Squares. The Annals of Statistics (1981) 465-474
- [29] S. Ghosh, et al, Taylor series approach for function approximation using ‘estimated’ higher derivatives. Applied Mathematics and Computation 284 (2016) 89–101
- [30] V. Strijova, G.W. Weber, Nonlinear regression model generation using hyperparameter optimization. Computers & Mathematics with Applications (2010) 981-988
- [31] Walpole E. Ronald, Myers H Raymond, Probability and Statistics for Engineers and Scientists. Macmillan (1972)
- [32] Zhuang Yu, at al., Statistical inference-based research on sampling time of vehicle driving cycle experiments. Transportation Research (2017) 114–141

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bwmeta1.element.psjd-620c637e-00a4-4718-9cd6-4bea546ff95c