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Journal articles on the topic 'Estimation of efficiency'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Liu, Bing, Zhen Chen, Xiangdong Liu, and Fan Yang. "An Efficient Nonlinear Filter for Spacecraft Attitude Estimation." International Journal of Aerospace Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/540235.

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Increasing the computational efficiency of attitude estimation is a critical problem related to modern spacecraft, especially for those with limited computing resources. In this paper, a computationally efficient nonlinear attitude estimation strategy based on the vector observations is proposed. The Rodrigues parameter is chosen as the local error attitude parameter, to maintain the normalization constraint for the quaternion in the global estimator. The proposed attitude estimator is performed in four stages. First, the local attitude estimation error system is described by a polytopic linea

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ÇINAR, Feyza, and Abdullah Çağrı BIBER. "The relationship between students' computational estimation skills and mathematical self-efficiency." Acta Didactica Napocensia 17, no. 1 (2024): 84–97. http://dx.doi.org/10.24193/adn.17.1.7.

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The factors related to estimating skills are twofold: cognitive and affective perspectives. Perception of self-efficacy in mathematics, one of the affective factors, is essential for the individual's capacity, abilities, and self-belief in mathematics for the mathematics course. The present study examined the relationship between students' computational estimation skills and mathematical self-efficacy perceptions. For this purpose, two sets of instruments were used as data collection tools: a computational estimation skills task and a mathematical self-efficacy perceptions scale. A correlation

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Hansen, Bruce E. "SHRINKAGE EFFICIENCY BOUNDS." Econometric Theory 31, no. 4 (2014): 860–79. http://dx.doi.org/10.1017/s0266466614000693.

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This paper is an extension of Magnus (2002, Econometrics Journal 5, 225–236) to multiple dimensions. We consider estimation of a multivariate normal mean under sum of squared error loss. We construct the efficiency bound (the lowest achievable risk) for minimax shrinkage estimation in the class of minimax orthogonally invariate estimators satisfying the sufficient conditions of Efron and Morris (1976, Annals of Statistics 4, 11–21). This allows us to compare the regret of existing orthogonally invariate shrinkage estimators. We also construct a new shrinkage estimator which achieves substantia

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Saikkonen, Pentti. "Asymptotically Efficient Estimation of Cointegration Regressions." Econometric Theory 7, no. 1 (1991): 1–21. http://dx.doi.org/10.1017/s0266466600004217.

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An asymptotic optimality theory for the estimation of cointegration regressions is developed in this paper. The theory applies to a reasonably wide class of estimators without making any specific assumptions about the probability distribution or short-run dynamics of the data-generating process. Due to the nonstandard nature of the estimation problem, the conventional minimum variance criterion does not provide a convenient measure of asymptotic efficiency. An alternative criterion, based on the concentration or peakedness of the limiting distribution of an estimator, is therefore adopted. The

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Rungsuriyawiboon, Supawat, and Spiro E. Stefanou. "Dynamic Efficiency Estimation." Journal of Business & Economic Statistics 25, no. 2 (2007): 226–38. http://dx.doi.org/10.1198/073500106000000288.

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Ouyang, Z., and H. T. Schreuder. "Approximate Srivastava Estimation in Forestry." Forest Science 39, no. 2 (1993): 309–20. http://dx.doi.org/10.1093/forestscience/39.2.309.

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Abstract Srivastava estimation formalizes the introduction of additional prior and posterior information in sampling to increase efficiency in estimation. An unbiased new estimator is given for Poisson sampling which is approximately as efficient as the standard slightly biased estimator without using any additional information. The increased efficiency possible with this method or approximations to it are illustrated for Poisson sampling and point-Poisson sampling using simulations. Srivastava estimation may be applicable in many forest inventory situations. Besides efficiency, the seriousnes

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Gillard, Nicolas, Étienne Belin, and François Chapeau-Blondeau. "Stochastic Resonance with Unital Quantum Noise." Fluctuation and Noise Letters 18, no. 03 (2019): 1950015. http://dx.doi.org/10.1142/s0219477519500159.

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The fundamental quantum information processing task of estimating the phase of a qubit is considered. Following quantum measurement, the estimation efficiency is evaluated by the classical Fisher information which determines the best performance limiting any estimator and achievable by the maximum likelihood estimator. The estimation process is analyzed in the presence of decoherence represented by essential quantum noises that can affect the qubit and belonging to the broad class of unital quantum noises. Such a class especially contains the bit-flip, the phase-flip, the depolarizing noises,

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ZHAO, Chaofan, Xiukai YUAN, and Jingqiang CHEN. "Structural global failure probability function estimation based on adaptive augmented line sampling method." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 41, no. 1 (2023): 105–14. http://dx.doi.org/10.1051/jnwpu/20234110105.

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A global failure probability function estimation method based on the adaptive augmented line sampling method is proposed to solve the parameter failure probability functions in structural reliability analysis and design. The proposed method uses an adaptive strategy to carry out a series of local failure probability function estimations at specific values in the design parameter space by using the augmented line sampling method. Then an optimal combination algorithm based on the minimum variation of coefficient is proposed to integrate all the local failure probability function estimations int

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9

Li, Xiaoou, and Gongjun Xu. "Uniformly efficient simulation for extremes of Gaussian random fields." Journal of Applied Probability 55, no. 1 (2018): 157–78. http://dx.doi.org/10.1017/jpr.2018.11.

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AbstractIn this paper we consider the problem of simultaneously estimating rare-event probabilities for a class of Gaussian random fields. A conventional rare-event simulation method is usually tailored to a specific rare event and consequently would lose estimation efficiency for different events of interest, which often results in additional computational cost in such simultaneous estimation problems. To overcome this issue, we propose a uniformly efficient estimator for a general family of Hölder continuous Gaussian random fields. We establish the asymptotic and uniform efficiency of the pr

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Al-Omari, Amer Ibrahim, SidAhmed Benchiha, and Ibrahim M. Almanjahie. "Efficient Estimation of Two-Parameter Xgamma Distribution Parameters Using Ranked Set Sampling Design." Mathematics 10, no. 17 (2022): 3170. http://dx.doi.org/10.3390/math10173170.

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An efficient method such as ranked set sampling is used for estimating the population parameters when the actual observation measurement is expensive and complicated. In this paper, we consider the problem of estimating the two-parameter xgamma (TPXG) distribution parameters under the ranked set sampling as well as the simple random sampling design. Various estimation methods, including the weighted least-square estimator, maximum likelihood estimators, least-square estimator, Cramer–von Mises, the maximum product of spacings estimators, and Anderson–Darling estimators, are considered. A compa

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Sarhad Ullah Khan, Muhammad Hanif, and Kalim Ullah. "REGRESSION-BASED MEAN ESTIMATOR UTILIZING RANK AND EMPIRICAL DISTRIBUTION FUNCTION BOTH AS DUALS OF A SINGLE AUXILIARY VARIABLE." Kashf Journal of Multidisciplinary Research 2, no. 02 (2025): 64–83. https://doi.org/10.71146/kjmr257.

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This study proposes a novel regression-type estimator for estimating the finite population mean under simple random sampling by incorporating both the rank and the empirical distribution function (EDF) as duals of a single auxiliary variable. The proposed estimator utilizes the distributional properties of the auxiliary variable to enhance estimation efficiency. Theoretical properties, including the mean square error (MSE) and bias of the estimator, are derived, and its efficiency is evaluated using real-life data. The results demonstrate the practical applicability and improved accuracy of th

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Pavlov, Alexander V. "Efficiency of team time estimation in project development." Accounting and control 9 (2025): 23–29. https://doi.org/10.36871/u.i.k.2025.09.01.003.

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This article discusses modern approaches to task completion time estimation, their strengths and weaknesses, and the impact of various factors on accuracy. Methods such as expert judgment, analogy, and statistical methods are considered, and examples of best practices that minimize the risks associated with estimation errors and improve the overall performance of the team are given. The complexity of time estimation is influenced by factors such as developer experience, task complexity, technical and organizational barriers, and subjective biases. The article describes several estimating metho

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Gur, Ohad. "Maximum Propeller Efficiency Estimation." Journal of Aircraft 51, no. 6 (2014): 2035–38. http://dx.doi.org/10.2514/1.c032557.

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14

Sedeeq, Bekhal Samad, Hogr Mohammed Qader, Azhy Akram Aziz, and Dlshad Mahmood Saleh. "Implementing a New Scale Technique in the M-Estimation Method to Estimate Parameters of Multiple Linear Regression: Simulation Study." Tikrit Journal of Administrative and Economic Sciences 19, no. 64, 1 (2023): 712–25. http://dx.doi.org/10.25130/tjaes.19.64.1.38.

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The goal of this study is to develop a new technique for estimating the parameters of a multiple linear regression by using M-estimation based on scale estimator to handle the influence of outlier values. In order to get new estimators, the root mean square error (RMSE) criterion is used to check the efficiency between the new technique and the classical method. The research showed that the new technique (M-estimation based on scale estimator) yields more accurate parameter estimates than the traditional approach (OLS) in all simulated cases.

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Arseniev, Vladimir, Anatolij Khomonenko, and Andrei Yadrenkin. "Weighed ranking of aprioristic and experimental data in control system functioning efficiency estimation problem with Pascal-distributed number of tests." Information and Control Systems, no. 3 (June 15, 2020): 39–47. http://dx.doi.org/10.31799/1684-8853-2020-3-39-47.

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Introduction: In order to steadily estimate the efficiency of control systems for new objects, a great number of prototypes should be tested, which is not always possible in practice. The estimation quality can be improved by joint processing of the a priori information you have before the tests by analyzing certain indicators, and the data obtained from the tests. To estimate the efficiency a posteriori, taking into account both the a priori knowledge and the test results, you have to find their functional dependence on each of them, and specify the parameters of this dependence. Purpose: Int

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Asghar, Amber, Aamir Sanaullah, Hina Khan, and Muhammad Hanif. "Comparative Analysis of Variance Estimation Methods in Two-Phase Sampling: A Focus on Regression-cum-Exponential Estimators with Multiple Auxiliaries." Bulletin of Business and Economics (BBE) 12, no. 3 (2023): 573–79. http://dx.doi.org/10.61506/01.00071.

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In this study, we introduce a regression-cum-exponential estimator designed for estimating population variance. Specifically, we focus on the estimation of unknown population variance in a two-phase sampling setup, considering the use of multiple auxiliary variables. We derive and discuss various cases pertaining to this estimation framework. Additionally, we compare the asymptotic properties of existing approaches with those of our proposed estimator. This allows us to assess the performance and efficiency of the different methods. Finally, we conduct a simulation study to evaluate the perfor

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Chen, Songnian, and Lung-Fei Lee. "EFFICIENT SEMIPARAMETRIC SCORING ESTIMATION OF SAMPLE SELECTION MODELS." Econometric Theory 14, no. 4 (1998): 423–62. http://dx.doi.org/10.1017/s026646669814402x.

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A semiparametric likelihood method is proposed for the estimation of sample selection models. The method is a two-step semiparametric scoring estimation procedure based on an index restriction and kernel estimation. Under some regularity conditions, the estimator is square-root n-consistent and asymptotically normal. The estimator is also asymptotically efficient in the sense that its asymptotic covariance matrix attains the semiparametric efficiency bound under the index restriction. For the binary choice sample selection model, it also attains the efficiency bound under the independence assu

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18

Williams, Michael S. "Improved estimation of domain totals in forest surveys." Canadian Journal of Forest Research 25, no. 7 (1995): 1203–7. http://dx.doi.org/10.1139/x95-133.

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The literature on estimating population totals in forest surveys is well developed. However in most practical applications, estimation of subpopulation totals (historically referred to as domains of study) is of equal or greater importance but receives much less attention. In this paper, techniques for estimating totals and variances for domains of study are reviewed and an adjusted estimator, with improved efficiency, is derived for estimating such totals. The properties of the adjusted and traditional estimator were studied using two populations, where each population contained three domains

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19

Igor, Lutsenko. "Cybernetic estimation of reserve utilization efficiency." Eastern-European Journal of Enterprise Technologies 6, no. 4 (114) (2021): 28–37. https://doi.org/10.15587/1729-4061.2021.245017.

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This study relates to the field of verification of cybernetic estimates of the use of reserves as criteria for the effectiveness of transformative class systems with a continuous supply of a technological product. The task set here attracted even more attention after the advent of improved approaches that make it possible to automatically change the control trajectories of technological systems in real time. In such cases, the assessment of the current status of the process and the efficiency of stock management has become an integral part of the operation of the management subsystems. Therefo

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20

Ikeda, Hajime, Taiga Sato, Kohei Yoshino, et al. "Deep Learning-Based Estimation of Muckpile Fragmentation Using Simulated 3D Point Cloud Data." Applied Sciences 13, no. 19 (2023): 10985. http://dx.doi.org/10.3390/app131910985.

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This research introduces an innovative technique for estimating the particle size distribution of muckpiles, a determinant significantly affecting the efficiency of mining operations. By employing deep learning and simulation methodologies, this study enhances the precision and efficiency of these vital estimations. Utilizing photogrammetry from multi-view images, the 3D point cloud of a muckpile is meticulously reconstructed. Following this, the particle size distribution is estimated through deep learning methods. The point cloud is partitioned into various segments, and each segment’s disti

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Myllymäki, Mari, Terje Gobakken, Erik Næsset, and Annika Kangas. "The efficiency of poststratification compared with model-assisted estimation." Canadian Journal of Forest Research 47, no. 4 (2017): 515–26. http://dx.doi.org/10.1139/cjfr-2016-0383.

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Survey sampling with model-assisted estimation has recently gained popularity in forest inventory. Another option for utilizing the auxiliary information is to use poststratification, which is a special case of model-assisted estimation with class variables as explanatory variables. In this study, we compared the efficiency of poststratification with an increasing number of strata with model-assisted estimation. We carried out a study based on a simulated population. We considered four different types of poststratifications, namely (i) stratification based on predictions of a linear model, (ii

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22

Adjekukor, A. J., and C. O. Aronu. "Robust Regression Estimation: A Doubly Weighted M-Estimation Approach with Generalized Jackknife Resampling." Asian Journal of Mathematics and Computer Research 32, no. 2 (2025): 27–35. https://doi.org/10.56557/ajomcor/2025/v32i29121.

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Robust regression estimation is crucial in addressing the influence of outliers and model misspecification in statistical modelling. This study proposes a Doubly Weighted M-Estimation (DWME) approach, integrating an adaptive weighting scheme with Generalized Jackknife Resampling (GJR) to enhance efficiency and robustness in parameter estimation. The DWME method incorporates case-specific and parameter-specific weighting functions, ensuring resistance against leverage points and heavy-tailed distributions. By leveraging GJR, the proposed estimator achieves reduced bias and variance while mainta

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Zheng, Yan Ping, Tian Tian, and Zhengang He. "Performance Parameter Estimation of the Parallel Hybrid Electric Vehicle." Applied Mechanics and Materials 130-134 (October 2011): 2180–84. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.2180.

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Based on the theory of HEV (Hybrid Electric Vehicle) and the idea of reverse simulation, the simulation model of the parallel HEV is established in MATLAB and the estimation of the energy efficiency, the power performance and the fuel economy of HEV is achieved, which provides reference for the performance estimation of parallel HEV. At the same time the definition and the estimating method about HEV energy efficiency were mentioned in this paper and the energy efficiency can be achieved by the simulation model. The results of the simulation show that this estimating method has certain practic

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Abonazel, Mohamed R., Mohamed Abdallah, and El-Housainy A. Rady. "On New Two-Step GMM Estimation of the Panel Vector Autoregressive Models with Missing observations." WSEAS TRANSACTIONS ON MATHEMATICS 21 (September 20, 2022): 671–83. http://dx.doi.org/10.37394/23206.2022.21.79.

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Few estimation methods were discussed to handle the missing data problem in the panel data models. However, in the panel vector autoregressive (PVAR) model, there is no estimator to handle this problem. The traditional treatment in the case of incomplete data is to use the generalized method of moment (GMM) estimation based on only available data without imputation of the missing data. Therefore, this paper introduces a new GMM estimation for the PVAR model in case of incomplete data based on the mean imputation. Moreover, we make a Monte Carlo simulation study to study the efficiency of the p

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Gabrousenko, Ye I., A. G. Holubnychyi, Zhengbing Hu, A. G. Taranenko, and F. J. Yanovsky. "ESTIMATION OF ELECTROMAGNETIC SHIELDING EFFICIENCY." Telecommunications and Radio Engineering 78, no. 2 (2019): 181–89. http://dx.doi.org/10.1615/telecomradeng.v78.i2.90.

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Popkin, Sarah H., Bohdan Z. Cybyk, Chase H. Foster, and Farrukh S. Alvi. "Experimental Estimation of SparkJet Efficiency." AIAA Journal 54, no. 6 (2016): 1831–45. http://dx.doi.org/10.2514/1.j052694.

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Asoodeh, Shahab, Mario Diaz, Fady Alajaji, and Tamas Linder. "Estimation Efficiency Under Privacy Constraints." IEEE Transactions on Information Theory 65, no. 3 (2019): 1512–34. http://dx.doi.org/10.1109/tit.2018.2865558.

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Han, Yongseung, and Myeong Hwan Kim. "The estimation of profit efficiency." Applied Economics Letters 25, no. 15 (2017): 1066–70. http://dx.doi.org/10.1080/13504851.2017.1397841.

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Buschmann, Ralf. "Efficiency of displacement estimation techniques." Signal Processing: Image Communication 10, no. 1-3 (1997): 43–61. http://dx.doi.org/10.1016/s0923-5965(97)00018-0.

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Jensen, D. R. "Vector efficiency in multiparameter estimation." Linear Algebra and its Applications 151 (June 1991): 143–55. http://dx.doi.org/10.1016/0024-3795(91)90360-9.

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31

Calzolari, Giorgio, Lorenzo Panattoni, and Claus Weihs. "Computational efficiency of FIML estimation." Journal of Econometrics 36, no. 3 (1987): 299–310. http://dx.doi.org/10.1016/0304-4076(87)90004-2.

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Chen, Willa W. "Efficiency in estimation of memory." Journal of Statistical Planning and Inference 140, no. 12 (2010): 3820–40. http://dx.doi.org/10.1016/j.jspi.2010.04.046.

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Popkova, O. S., Wu Linh Nguyen, O. S. Dmitrieva, I. N. Madyshev, and A. N. Nikolaev. "Estimation of Rectangular Separator Efficiency." Journal of Physics: Conference Series 1210 (March 2019): 012114. http://dx.doi.org/10.1088/1742-6596/1210/1/012114.

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SENGUPTA, JATI K., and RAYMOND E. SFEIR. "Estimation of portfolio efficiency frontiers." International Journal of Systems Science 17, no. 11 (1986): 1589–99. http://dx.doi.org/10.1080/00207728608926909.

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Connolly, J. "Efficiency of experimental designs for estimating common-row-and-column (CRAC) effects." Journal of Agricultural Science 124, no. 3 (1995): 325–34. http://dx.doi.org/10.1017/s0021859600073287.

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SUMMARYTwo factor designs are considered in which the levels of the two factors are linked (e.g. certain diallel cross and reciprocal transplant experiments). A common-row-and-column (CRAC) effect is defined as a systematic effect in the response when the treatment combination has the same level of the two factors. The efficiency of designs for estimating CRAC effects is discussed. Square designs with various levels of extra replication for CRAC treatment combinations and strand designs, based on omitting certain treatment combinations for which the two factors do not have the same level of th

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Fang, Yang, Xiaolong Wei, and Jianjun Ma. "High-Precision DOA Estimation Based on Synthetic Aperture and Sparse Reconstruction." Sensors 23, no. 21 (2023): 8690. http://dx.doi.org/10.3390/s23218690.

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The direction-of-arrival (DOA) estimation is predominantly influenced by the antenna’s aperture size. However, space constraints on flight platforms often necessitate the use of antennas with smaller apertures and fewer array elements. This inevitably imposes limitations on the DOA estimation’s resolution and degrees of freedom. To address these precision constraints, we introduce an accurate DOA estimation method based on spatial synthetic aperture model. This method adopts a two-stage strategy to ensure both efficiency and precision in DOA estimation. Initially, the orthogonal matching pursu

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Moyano, Henrry, and Luis Vargas. "The Efficiency of the Kalman Filter in Nodal Redundancy." Energies 17, no. 9 (2024): 2131. http://dx.doi.org/10.3390/en17092131.

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The growing integration of distributed energy resources underscores the critical importance of having precise insights into the dynamics of an electrical power system (EPS). Consequently, an estimator must align with the EPS dynamics to enhance the overall reliability, safety, and system stability. This alignment ensures that operators can make informed decisions during system operations. An initial step in gaining insight into the system’s state involves examining its state vector, which is represented by voltage phasors. These results are derived through the application of a distributed stat

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Youssef, Ahmed H., Mohamed R. Abonazel, and Amr R. Kamel. "Efficiency Comparisons of Robust and Non-Robust Estimators for Seemingly Unrelated Regressions Model." WSEAS TRANSACTIONS ON MATHEMATICS 21 (May 6, 2022): 218–44. http://dx.doi.org/10.37394/23206.2022.21.28.

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This paper studies and reviews several procedures for developing robust regression estimators of the seemingly unrelated regressions (SUR) model, when the variables are affected by outliers. To compare the robust estimators (M-estimation, S-estimation, and MM-estimation) with non-robust (traditional maximum likelihood and feasible generalized least squares) estimators of this model with outliers, the Monte Carlo simulation study has been performed. The simulation factors of our study are the number of equations in the system, the number of observations, the contemporaneous correlation among eq

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Rauf, Rauf I., Alabi O. Olusegun, Bello A. Hamidu, Bodunwa O. Kikelomo, and Ayinde Kayode. "New Approach in Stochastic Frontier Analysis Estimation for Addressing Joint Assumption Violation of Heteroscedasticity and Multicollinearity." Asian Journal of Probability and Statistics 26, no. 9 (2024): 9–26. http://dx.doi.org/10.9734/ajpas/2024/v26i9643.

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Efficiency analysis in production units has long been a key area of interest in economics, particularly with the development of methodologies like Stochastic Frontier Analysis (SFA). Originating from seminal works by Aigner & Cain (1977) and Meeusen & Van Den Broeck (1977), SFA has been instrumental in assessing the efficiency of entities by separating technical inefficiency from random production fluctuations. Despite its widespread application, the SFA model faces challenges, especially when underlying assumptions such as multicollinearity and heteroscedasticity are violated. This st

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Sertsöz, Mine, Mehmet Fidan, and Mehmet Kurban. "Three autoregressive-neural network hybrid models for energy efficiency estimation of induction motors." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 38, no. 1 (2019): 431–51. http://dx.doi.org/10.1108/compel-02-2018-0093.

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Purpose Improvements on the energy efficiency of the induction motors bear on not only these motors but also on the whole industry as a result of preference of these types of motors. In recent projects, energy efficiency of the induction motors is approaching to 90 per cent. The first necessary condition of the efficiency improvements is an accurate estimation of energy efficiency. This study aims to estimate the energy efficiency of induction motors by using three innovative estimation methods. Design/methodology/approach Data for 307 motors were taken from three different companies and their

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Awwal, Adejumobi Mojeed Abiodun Yunusa. "An Efficient Exponential Estimator of Population Mean in the Presence of Median of the Study Variable." LC International Journal of STEM 3, no. 4 (2023): 25–39. https://doi.org/10.5281/zenodo.7607094.

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Survey sampling practitioners have been functioning on efficiency improvement and bias reduction in finite population parameter estimation. We proposed an exponential estimator of a population means in the presence of the median of the study variable. The bias and mean square error of the proposed estimator were obtained using the Taylor series method. The relative performance of the proposed estimators concerning conventional and some existing estimators was assessed using three (3) natural dataset information. The novel median-based estimator accomplishes better than the conventional, usual

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Alghamdi, Abdulaziz S., and Fatimah A. Almulhim. "Improved Median Estimation in Stratified Surveys via Nontraditional Auxiliary Measures." Symmetry 17, no. 7 (2025): 1136. https://doi.org/10.3390/sym17071136.

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This research focuses on estimating the population median within a stratified random sampling framework by using robust statistical measures with transformation-based methodologies. An efficient estimator aims to minimize both the bias and the variance, thereby reducing the overall mean squared error (MSE, leading to more reliable outcomes. We introduce an improved class of proposed estimators that utilizes transformation techniques to effectively address data variability and enhance estimation accuracy. To evaluate their performance, we derive expressions for bias and mean square error (MSE)

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Kareem, Urdak, and Fadhaa Hashim. "The Use Of Genetic Algorithm In Estimating The Parameter Of Finite Mixture Of Linear Regression." Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), no. 1 (June 29, 2022): 237–52. http://dx.doi.org/10.55562/jrucs.v51i1.536.

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The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the e

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Utomo, Bayu, Nanang Kusnandar, Himma Firdaus, et al. "Comparison of GUM and Monte Carlo Methods for Measurement Uncertainty Estimation of the Energy Performance Measurements of Gas Stoves." Measurement Science Review 22, no. 4 (2022): 160–69. http://dx.doi.org/10.2478/msr-2022-0020.

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Abstract The paper presents the comparison of uncertainty measurement estimations of the energy performances of gas stoves. The Guide to the Expression of Uncertainty in Measurement (GUM) framework and two Monte Carlo Simulation (MCM) approaches: ordinary and adaptive MCM were applied for the energy performance uncertainty: thermal energy and efficiency measurement uncertainties. The validation of the two MCMs is performed by comparing the MCM estimations to the GUM estimations for the thermal energy and efficiency measurement results. A test method designed in Indonesia National Standard SNI

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Rady, El-Housainy A., Mohamed Abdallah, and Mohamed R. Abonazel. "A Proposed Generalized Method of Moment Estimation of the Panel Vector Autoregressive Model with Missing Data." Journal of Computational and Theoretical Nanoscience 18, no. 6 (2021): 1730–36. http://dx.doi.org/10.1166/jctn.2021.9721.

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Estimation methods to handle missing data problems in various panel data models are rarely discussed. However in the panel vector autoregressive model, there is no estimator to handling this type of problems. The traditional treatment for cases of involving incomplete data is to use generalized method of moment estimation based only on the available data without imputation the missing data. Thus, this study introduces a generalized method of moment estimator for the panel vector autoregressive model for solving problems involving incomplete dataset. Our proposed estimator is based on mean impu

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46

Rady, El-Housainy A., Mohamed Abdallah, and Mohamed R. Abonazel. "A Proposed Generalized Method of Moment Estimation of the Panel Vector Autoregressive Model with Missing Data." Journal of Computational and Theoretical Nanoscience 18, no. 6 (2021): 1730–36. http://dx.doi.org/10.1166/jctn.2021.9721.

Full text

Abstract:

Estimation methods to handle missing data problems in various panel data models are rarely discussed. However in the panel vector autoregressive model, there is no estimator to handling this type of problems. The traditional treatment for cases of involving incomplete data is to use generalized method of moment estimation based only on the available data without imputation the missing data. Thus, this study introduces a generalized method of moment estimator for the panel vector autoregressive model for solving problems involving incomplete dataset. Our proposed estimator is based on mean impu

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47

Patel, Nirav, and Vijay Patel. "Innovative Approach of Spectral Efficiency Optimization over Various Pilot Reuse Factors." International Journal of Electrical and Electronics Research 11, no. 4 (2023): 1001–12. http://dx.doi.org/10.37391/ijeer.110418.

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The Massive MIMO with TDD is breakthrough technology for spectral efficiency gains. The CSI is essential for spectral efficiency gains and CSI can be obtained by channel estimation methods. The channel estimation methods employ known pilot s sequences to estimate the channel before actual data transmission. However, the channel coherence is time and frequency limited, which reflects the trade-off between the resources available for pilots and those available for data in coherent block for transmission. The pilot sequences reuse in other cells can reduce pilot overhead, called pilot reuse. Howe

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Melnyk, Igor, Alina Pochynok, and Mykhailo Skrypka. "Comparison of methods for interpolation and extrapolation of boundary trajectories of short-focus electron beams using root-polynomial functions." System research and information technologies, no. 3 (September 28, 2024): 74–92. http://dx.doi.org/10.20535/srit.2308-8893.2024.3.05.

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The article considers and discusses the comparison of interpolation and extrapolation methods of estimation of the boundary trajectory of electron beams propagated in ionized gas. All estimations have been computed using root-polynomial functions to numerically solve a differential-algebraic system of equations that describe the boundary trajectory of the electron beam. By providing analysis, it is shown and proven that in the case of solving a self-connected interpolation-extrapolation task, the average error of the beam radius estimation is generally smaller. This approach was especially eff

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Hamza, Muhammad, and Shakeel Ahmed. "Stratum-specific health outcome estimation in Pakistan using double goal CART." PLOS ONE 19, no. 2 (2024): e0294736. http://dx.doi.org/10.1371/journal.pone.0294736.

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Post-stratification is applied when the subpopulation membership is observed only for sampled values and the goal is to estimate stratum-specific parameters which leads the survey statisticians towards primary goals i.e., classification of non-sampled units into different strata and prediction of the values of the study variables. Regression models, on one side, optimize the prediction of the study variable’s non-sampled values while the classification algorithms, on the other side, look for the classification of non-sampled cases into different strata. Hence, it is crucial to deal with these

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Zhang, Sheng-Peng, and Tae-Oh Tak. "Efficiency Estimation of Roller Chain Power Transmission System." Applied Sciences 10, no. 21 (2020): 7729. http://dx.doi.org/10.3390/app10217729.

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In the present study, a novel approach to estimating the efficiency of roller chain power transmission systems is proposed based on sliding friction losses and damping force. The dynamics model is taken into account between chain links with lateral offset owing to the derailleur system. Frictional losses were calculated according to Coulomb’s law of friction, and the damping force was dependent on the damping coefficient. The effects of rotational speed, load, derailleur system, and damping coefficient on transmission efficiency were analyzed. The test stand of the roller chain power transmiss

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