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Artykuły w czasopismach na temat „Minimize the variance”

Autor: Grafiati

Data publikacji: 5 czerwca 2025

Data aktualizacji: 2 sierpnia 2025

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1

Filberg, D., and H. Kleindienst. "Orbitals that minimize the variance." Theoretica Chimica Acta 75, no. 6 (1989): 425–32. http://dx.doi.org/10.1007/bf00527674.

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Danish, Faizan, Rafia Jan, Muhammad Daniyal, and Kassim Tawiah. "Optimum Stratification Using Dynamic Programming with a Mixture of Ratio and Product Estimators under Super Population Model." Mathematical Problems in Engineering 2023 (April 29, 2023): 1–10. http://dx.doi.org/10.1155/2023/3149912.

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In this study, we have utilized two study variables and one auxiliary variable. The auxiliary variable is used as the stratification variable, and we selected the sample using the stratification variable with a mixture of ratio and product estimators. Under super population set-up, minimal equations have been obtained through minimization of the aggregated variance with the help of the variables under study. The objective function is minimized with respect to the constraints under consideration. The dynamic programming approach has been used to minimize the variance and obtain the optimum stra

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RAMIREZ-MARQUEZ, JOSE E., DAVID W. COIT, and TONGDAN JIN. "TEST PLAN ALLOCATION TO MINIMIZE SYSTEM RELIABILITY ESTIMATION VARIABILITY." International Journal of Reliability, Quality and Safety Engineering 11, no. 03 (2004): 257–72. http://dx.doi.org/10.1142/s0218539304001506.

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A new methodology is presented to allocate testing units to the different components within a system when the system configuration is fixed and there are budgetary constraints limiting the amount of testing. The objective is to allocate additional testing units so that the variance of the system reliability estimate, at the conclusion of testing, will be minimized. Testing at the component-level decreases the variance of the component reliability estimate, which then decreases the system reliability estimate variance. The difficulty is to decide which components to test given the system-level

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4

Marangos, Charalambos A., Vinay Govande, G. Srinivasan, and Emory W. Zimmers. "Algorithms to minimize completion time variance in a two machine flowshop." Computers & Industrial Engineering 35, no. 1-2 (1998): 101–4. http://dx.doi.org/10.1016/s0360-8352(98)00030-8.

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Falconer, David D. "Linear Precoding of OFDMA Signals to Minimize Their Instantaneous Power Variance." IEEE Transactions on Communications 59, no. 4 (2011): 1154–62. http://dx.doi.org/10.1109/tcomm.2011.11.100042.

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Li, Xueping, Nong Ye, Tieming Liu, and Yang Sun. "Job scheduling to minimize the weighted waiting time variance of jobs." Computers & Industrial Engineering 52, no. 1 (2007): 41–56. http://dx.doi.org/10.1016/j.cie.2006.10.010.

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Ma, Xiangqi. "Optimal Portfolio with Pension under Three Models: Mean-Variance, CAPM and FF3F." BCP Business & Management 35 (December 31, 2022): 723–29. http://dx.doi.org/10.54691/bcpbm.v35i.3376.

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In recent years, an increasing number of people are investing their money to increase their total wealth and maintain their quality of life after retirement. How to choose the optimal portfolio is a key part of financial management. This study chooses six assets which performs relative well in different industries together with one’s pension which is regarded as an asset accounting for a solid weight. This paper uses three models: Mean-Variance analysis, CAPM and FF3F model to build the optimal portfolio to maximize sharp ratio and minimize variance respectively. The result shows that, in the

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Blanc, Sebastian M., and Thomas Setzer. "Bias–Variance Trade-Off and Shrinkage of Weights in Forecast Combination." Management Science 66, no. 12 (2020): 5720–37. http://dx.doi.org/10.1287/mnsc.2019.3476.

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Combining forecasts is an established approach for improving forecast accuracy. So-called optimal weights (OWs) estimate combination weights by minimizing errors on past forecasts. Yet the most successful and common approach ignores all training data and assigns equal weights (EWs) to forecasts. We analyze this phenomenon by relating forecast combination to statistical learning theory, which decomposes forecast errors into three components: bias, variance, and irreducible error. In this framework, EWs minimize the variance component (errors resulting from estimation uncertainty) but ignore the

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9

Adi Wibowo, Seto Sulaksono, Dwi Amelia Putri, and Yosi Handayani. "Cost Budget Variance." JURNAL AKUNTANSI, EKONOMI dan MANAJEMEN BISNIS 9, no. 1 (2021): 60–64. http://dx.doi.org/10.30871/jaemb.v9i1.3154.

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The research was conducted at the Scanner Engineering Department of PT Epson Batam. The topic is written about budget management for repair and maintenance (die & mold) costs with the aim of knowing how to minimize the variance between budgeted costs and their realization. Data collection methods used in this study were interviews, observation, and documentation, and descriptive and quantitative methods were used for data analysis. The existing budgeting system in the Scanner Engineering Department has been carried out correctly and effectively met the objectives, but overall during the 20

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10

Bin, Wan Yang Bai*. "THE INPUT-OUTPUT MODEL WITH RESOURCE CONSTRAINT EXTENSION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 9, no. 6 (2020): 10–11. https://doi.org/10.29121/ijesrt.v9.i6.2020.3.

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In this paper, we inspired by optimization of margin distributions theoretical result, which can maximize the mean and simultaneously minimize the variance. Then, the Lagrangian algorithm approach is presented to solve the problem.

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11

Wang, Chunji, Yupeng Xiao, Etienne Burdet, James Gordon, and Nicolas Schweighofer. "The duration of reaching movement is longer than predicted by minimum variance." Journal of Neurophysiology 116, no. 5 (2016): 2342–45. http://dx.doi.org/10.1152/jn.00148.2016.

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Whether the central nervous system minimizes variability or effort in planning arm movements can be tested by measuring the preferred movement duration and end-point variability. Here we conducted an experiment in which subjects performed arm reaching movements without visual feedback in fast-, medium-, slow-, and preferred-duration conditions. Results show that 1) total end-point variance was smallest in the medium-duration condition and 2) subjects preferred to carry out movements that were slower than this medium-duration condition. A parsimonious explanation for the overall pattern of end-

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12

Zheng, Zichun. "Application of LSTM and portfolio optimization in Chinese stock market." BCP Business & Management 30 (October 24, 2022): 380–87. http://dx.doi.org/10.54691/bcpbm.v30i.2450.

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The purpose of this paper is to examine the application of LSTM and mean variance portfolio optimization in Chinese stock market. 20 stocks are selected from CSI 300 components, we collect their High, Low, Open, Adjust Close and trade volume from June 16th 2020 to June 16th 2022. Then we use LSTM model to forecast the stock price. The forecast results are used to construct 2 portfolios. One portfolio maximize Sharpe ratio, the other portfolio minimize variance. From April 6th to June 16th 2022, the Maximize Sharpe Ratio portfolio outperformed CSI 300 index, the Minimize Variance Portfolio did

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13

Wang, Chenggang, Zengfu Wang, Xiong Xu, and Yuhang Hao. "A balanced sensor scheduling for multitarget localization in a distributed multiple-input multiple-output radar network." International Journal of Distributed Sensor Networks 17, no. 7 (2021): 155014772110301. http://dx.doi.org/10.1177/15501477211030121.

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In this article, we consider the problem of optimally selecting a subset of transmitters from a transmitter set available to a multiple-input and multiple-output radar network. The aim is to minimize the location estimation error of underlying targets under a power constraint. We formulate it as a minimum-variance estimation problem and show that the underlying variance reduction function is submodular. From the properties of submodularity, we present a balanced selection policy which minimizes the worst-case error value using a minimax strategy. A greedy algorithm with guaranteed performance

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14

Guo, Qin Zhen, Zhi Zeng, and Shu Wu Zhang. "Uniform Variance Product Quantization." Applied Mechanics and Materials 651-653 (September 2014): 2224–27. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.2224.

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Product quantization (PQ) is an efficient and effective vector quantization approach to fast approximate nearest neighbor (ANN) search especially for high-dimensional data. The basic idea of PQ is to decompose the original data space into the Cartesian product of some low-dimensional subspaces and then every subspace is quantized separately with the same number of codewords. However, the performance of PQ depends largely on the distribution of the original data. If the distributions of every subspace have larger difference, PQ will achieve bad results as shown in our experiments. In this paper

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15

FURUYA, Kohei, Jun SAKAMOTO, Akihiko KATAGIRI, and Takeshi TOI. "Robust design to minimize FRF variance of structure by stochastic finite element method." Transactions of the JSME (in Japanese) 80, no. 810 (2014): DR0030. http://dx.doi.org/10.1299/transjsme.2014dr0030.

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Cai, X. "V-shape property for job sequences that minimize the expected completion time variance." European Journal of Operational Research 91, no. 1 (1996): 118–23. http://dx.doi.org/10.1016/0377-2217(95)00097-6.

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17

BIAGINI, FRANCESCA, and BERNT ØKSENDAL. "MINIMAL VARIANCE HEDGING FOR INSIDER TRADING." International Journal of Theoretical and Applied Finance 09, no. 08 (2006): 1351–75. http://dx.doi.org/10.1142/s0219024906003998.

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In this paper, we first study the problem of minimal hedging for an insider trader in incomplete markets. We use the forward integral in order to model the insider portfolio and consider a general larger filtration. We characterize the optimal strategy in terms of a martingale condition. In the second part we focus on a problem of mean-variance hedging where the insider tries to minimize the variance of his wealth at time T given that this wealth has a fixed expected value A. We solve this problem for an initial enlargement of filtration by providing an explicit solution.

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18

Li, Zheng. "A Time-Varying Generalized Minimum Variance Controller for Servo Application." Applied Mechanics and Materials 278-280 (January 2013): 1403–8. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.1403.

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A generalized minimum variance controller is developed for linear time-varying systems for servo applications. The plants to be controlled is described using a SISO CARMA model and the control objective is to minimize a generalized minimum variance performance index, where the output tracking error variance is penalized by squared incremental of plant input in order to reduce fluctuation in plant input and attenuate process disturbances.

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Li, Zheng, and Guo Li Wang. "A Time-Varying MIMO Generalized Minimum Variance Controller for Servo Application." Applied Mechanics and Materials 321-324 (June 2013): 1593–96. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.1593.

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A generalized minimum variance controller is developed for multiple input and multiple output systems having time-varying dynamics. The plant to be controlled is described using a controlled autoregressive moving average model and the control objective is to minimize a generalized minimum variance performance index for servo applications.

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20

Patrisya Putri Utami, Amira Dwi Aryani, Nur Aini Putri Daryanti, Siti Hindun, and Azahra Elsa Mayori. "Analisis Faktor Pemicu Selisih Anggaran dengan Pendapatan Direktorat Jendral Hortikultura." Inisiatif: Jurnal Ekonomi, Akuntansi dan Manajemen 4, no. 1 (2024): 209–18. https://doi.org/10.30640/inisiatif.v4i1.3493.

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This study aims to analyze the implementation of the budget and the factors triggering the budget variance in the Directorate General of Horticulture, Ministry of Agriculture of the Republic of Indonesia. Inaccuracies in budget planning and management can lead to deficits that affect operations and the success of programs. This research uses secondary data in the form of budget realization reports from 2020, with descriptive analysis methods to illustrate the variance between the budget and revenue. The results show that fluctuations in commodity prices, policy changes, and inaccuracies in bud

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21

Bentahar, Tarek, Djamel Benatia, and Mohamed Boulila. "De-noising interferogram inSAR using variance and absolute deviation functions." World Journal of Engineering 13, no. 2 (2016): 169–76. http://dx.doi.org/10.1108/wje-04-2016-022.

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Purpose In this paper, a new efficient method to de-noise the interferometric Synthetic Aperture Radar interferogram, also called wrapped phase image, is proposed with the aim to reduce the residue number and make the phase unwrapping process easy. Design/methodology/approach This method is based on two statistics functions, the former is the phase derivative variance (PDV) defined as a quality map to select the badness areas, the second one is the phase derivative variance (PAD) for a local 3 × 3 pixels filtering which allows to assign an estimated phase for each bad area selected by PDV func

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Fernandes, C., and P. Ramos. "A METHOD TO MINIMIZE THE SUM OF THE VARIANCES OF THE ESTIMATORS OF THE VARIANCE COMPONENTS IN STAIR NESTED DESIGNS." Advances and Applications in Statistics 51, no. 4 (2017): 277–82. http://dx.doi.org/10.17654/as051040277.

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Agustina, Dina, Devni Prima Sari, Rara Sandhy Winanda, Muhammad Rashif Hilmi, and Dina Fakhriyana. "Comparison of Portfolio Mean-Variance Method with the Mean-Variance-Skewness-Kurtosis Method in Indonesia Stocks." EKSAKTA: Berkala Ilmiah Bidang MIPA 23, no. 02 (2022): 88–97. http://dx.doi.org/10.24036/eksakta/vol23-iss02/316.

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In this paper, we compare the optimal portfolio weight of mean-variance (MV) method with mean-variance-skewness-kurtosis (MVSK) method. MV is a method to get weight on a portfolio. This method can be developed into the method of MVSK with attention to the higher-order moment of return distribution; skewness and kurtosis. In determining the weight of portfolio is also important to consider the skewness and kurtosis of return distribution. This method of considering the aspect of skewness and kurtosis is called the MVSK method with the aim of maximizing the level of return and skewness and minim

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24

Vos, Paul, and Qiang Wu. "Maximum likelihood estimators uniformly minimize distribution variance among distribution unbiased estimators in exponential families." Bernoulli 21, no. 4 (2015): 2120–38. http://dx.doi.org/10.3150/14-bej637.

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KATAGIRI, Akihiko, and Takeshi TOI. "Robust design to minimize eigen frequency variance of structure by stochastic finite element method." Transactions of the JSME (in Japanese) 80, no. 819 (2014): DR0329. http://dx.doi.org/10.1299/transjsme.2014dr0329.

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Han, Xia, Zhibin Liang, and Virginia R. Young. "Optimal reinsurance to minimize the probability of drawdown under the mean-variance premium principle." Scandinavian Actuarial Journal 2020, no. 10 (2020): 879–903. http://dx.doi.org/10.1080/03461238.2020.1788136.

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Viswanathkumar, G., and G. Srinivasan. "A branch and bound algorithm to minimize completion time variance on a single processor." Computers & Operations Research 30, no. 8 (2003): 1135–50. http://dx.doi.org/10.1016/s0305-0548(02)00062-x.

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Liang, Xiaoqing, Zhibin Liang, and Virginia R. Young. "Optimal reinsurance under the mean–variance premium principle to minimize the probability of ruin." Insurance: Mathematics and Economics 92 (May 2020): 128–46. http://dx.doi.org/10.1016/j.insmatheco.2020.03.008.

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HARYONO, NADIA ASANDIMITRA, and M. RIADHOS SOLICHIN. "Efektivitas Strategi Hedging Menggunakan Kontrak Indeks Lq45 Futures dalam Meminimalisasi Risiko Sistematis Portofolio." BISMA (Bisnis dan Manajemen) 2, no. 2 (2018): 100. http://dx.doi.org/10.26740/bisma.v2n2.p100-106.

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AbstractInvestor can make hedging to the systematic risk or market risk by using LQ45 index futures contract whose value comparable to the share portfolio value they have. This research had the purpose to prove used the LQ45 index futures contract in minimize the portfolio systematic risk. In this research used LQ45 index as the proxy on the portfolio have been properly diversified. Data used in this research were LQ45 index daily value data and the daily closing price of LQ45 index futures with 2004-2005 research period. Testing was conducted by comparing the portfolio return hedged variance

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Liu, Yang, Brandon M. Sexton, and Hannah J. Block. "Spatial bias in estimating the position of visual and proprioceptive targets." Journal of Neurophysiology 119, no. 5 (2018): 1879–88. http://dx.doi.org/10.1152/jn.00633.2017.

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When people match an unseen hand to a visual or proprioceptive target, they make both variable and systematic (bias) errors. Variance is a well-established factor in behavior, but the origin and implications of bias, and its connection to variance, are poorly understood. Eighty healthy adults matched their unseen right index finger to proprioceptive (left index finger) and visual targets with no performance feedback. We asked whether matching bias was related to target modality and to the magnitude or spatial properties of matching variance. Bias errors were affected by target modality, with s

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Albayyat, Ramlah H., Hajar S. Aljohani, and Dalia K. Alnagar. "A new estimator of between study variance of standardized mean difference in meta-analysis." PLOS ONE 19, no. 11 (2024): e0308628. http://dx.doi.org/10.1371/journal.pone.0308628.

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Meta-analysis is a statistical technique that combines the results of different environmental experiments regarding the populations, location, time, and so on. These results will differ more than the within-study variance, and the true effects being evaluated differ between studies. Thus, heterogeneity is present and should be measured. There are different estimators that were introduced to estimate between-study variance, which has received a lot of criticism from previous researchers. All of the estimators encountered the same problem, which was the correlation. To minimize the potential bia

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El Attar, Abderrahim, Mostafa El Hachloufi, and Zine El Abidine Guennoun. "Optimal Reinsurance through Minimizing New Risk Measures under Technical Benefit Constraints." International Journal of Engineering Research in Africa 35 (March 2018): 24–37. http://dx.doi.org/10.4028/www.scientific.net/jera.35.24.

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In this paper we present an approach to minimize the actuarial risk for the optimal choice of a form of reinsurance, and this is intended to be through a choice of treated parameters that minimize the risk using the Conditional Tail Expectation and the Conditional Tail Variance risk measures. The minimization procedure is based on the Augmented Lagrangian and a genetic algorithm with technical benefit as a constraint. This approach can be seen as a decision support tool that can be used by managers to minimize the actuarial risk in the insurance company.

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Jayeola, Dare, Peter O. Olatunji, and Y. J. Aborisade. "Efficient Method for Assets Allocation." International Journal of Research and Innovation in Social Science IX, no. V (2025): 4308–13. https://doi.org/10.47772/ijriss.2025.905000329.

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Asset allocation requires allotting savings among many assets. The goal of investors is to minimize risk at a given returns or/and maximize returns at a specified risk. The aim of this paper is to compare two asset allocations, Black Litterman model (BLM) and Mean Variance Model (MVM). The data used are groundnut oil, palm oil and palm kernel oil. The data is used to estimate values of risk and returns using both asset allocations to estimate risk and return of the three assets. It is observed that BLM minimizes risk and maximizes the return of its portfolio better than MVM.

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Regina, Filippo, and Mauro Gianfranco Bisceglia. "A-KA Model: an Optimization of the Stock’s Portofolio." Zagreb International Review of Economics and Business 23, no. 2 (2020): 21–40. http://dx.doi.org/10.2478/zireb-2020-0012.

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AbstractThe elaborate proposes a compact alternative methodology to the classical stocks portfolio optimization based on the normal distribution of the returns of the assets named Adaptable - Kurtosis Asymmetry model (A-KA). In the financial theory is well-known that odd-order moments of a distribution describe a particular performance characteristic; on the contrary, the even-order moments tell a precise sense of risk of a distribution of returns. If it is true that, in general terms, minimizing the variance also minimizes the volatility of portfolio return is also true that we should minimiz

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Yang, Yuchen, Jun Zhou, and Xiaotong Chen. "Variance reduction in Monte Carlo for Integrals." Theoretical and Natural Science 53, no. 1 (2024): 203–15. http://dx.doi.org/10.54254/2753-8818/53/20240205.

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Abstract. Nowadays, the extensive use of Monte Carlo methods in various fields has promoted the scientific decision-making, improved the efficiency of social operation, and enabled better management of many uncertain factors in daily life. However, in some cases, traditional Monte Carlo methods doesn't work so well because of the excessive variance. This paper aims to explore a new numerical integration method called splitting method to minimize intrinsic variance in Monte Carlo simulations. Through this innovative method, we found that the variance was reduced significantly. Despite some osci

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Curtis, Christopher D., and Sebastián M. Torres. "Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar." Journal of Atmospheric and Oceanic Technology 28, no. 12 (2011): 1581–97. http://dx.doi.org/10.1175/jtech-d-10-05042.1.

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Abstract This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2 while producing meteorological data with similar quality. Adaptive range oversampling uses moment-specific transformations to minimize the variance of meteorological variable estimates. An efficient algorithm is introduced that allows for seamless integration with other signal processing f

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Ingram, Ian, Aaron M. Thode, and Nicholas C. Makris. "Minimum samples sizes required to minimize variance and bias of geoacoustic estimates of seafloor properties." Journal of the Acoustical Society of America 109, no. 5 (2001): 2423. http://dx.doi.org/10.1121/1.4744578.

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Al-Anzi, Fawaz S., and Ali Allahverdi. "Using a Hybrid Evolutionary Algorithm to Minimize Variance in Response Time for Multimedia Object Requests." Journal of Mathematical Modelling and Algorithms 4, no. 4 (2005): 435–53. http://dx.doi.org/10.1007/s10852-005-9027-9.

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Anoop Kumar. "Optimizing Photometric Light Curve Analysis: Evaluating Scipy's Minimize Function for Eclipse Mapping of Cataclysmic Variables." Journal of Electrical Systems 20, no. 7s (2024): 2557–66. http://dx.doi.org/10.52783/jes.4079.

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With a particular focus on Scipy's minimize function—the eclipse mapping method is thoroughly researched and implemented utilizing Python and essential libraries. Many optimization techniques are used, including Sequential Least Squares Programming (SLSQP), Nelder-Mead, and Conjugate Gradient (CG). However, for the purpose of examining photometric light curves—these methods seek to solve the maximum entropy equation under a chi-squared constraint. Therefore, these techniques are first evaluated on two-dimensional Gaussian data without a chi-squared restriction, and then they are used to map th

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Raharjanti, Amalia. "Mean-Variance Investment Without Risk-Free Assets in PT Company Shares PT Ace Hardware (Aces.Jk), PT Mayora Indah (Myor.Jk), PT Bri (Bbri.Jk), PT Siloam Hospital (Silo.Jk), PT Eterindo Wahanatama (Etwa.Jk)." Operations Research: International Conference Series 4, no. 3 (2023): 105–8. http://dx.doi.org/10.47194/orics.v4i3.251.

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Portfolio is a form of strategy that investors often apply in risky investment conditions. The essence of portfolio construction is to allocate funds to various investment options to minimize investment risk. Therefore, the aim of this discussion is to construct an investment portfolio of several shares using an average variable portfolio optimization model without risk-free assets. To obtain an optimal portfolio, a mean-variance investment optimization model without risk-free assets or what is called the Basic Markowitz model is used. This involves investors measuring the risk of an asset usi

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Olexandr, Turovsky. "ESTIMATION OF THE POSSIBILITIES OF THE COMBINED SYNCHRONIZATION SYSTEM WITH OPEN-LINK TO MINIMIZE THE DISPERSION OF THE PHASE ERROR WHEN TRACKING THE CARRIER FREQUENCY UNDER THE CONDITIONS OF THE INFLUENCE OF ADDITIVE NOISE." TECHNOLOGY AUDIT AND PRODUCTION RESERVES 4, no. 1 (54) (2020): 16–22. https://doi.org/10.15587/2706-5448.2020.210242.

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The object of the article is the process of evaluating the possibilities of a combined synchronization system with open (compensating) connection to minimize the phase error variance under the influence of additive Gaussian noise. The issue of improving the quality of the phase synchronization system is a constant topical scientific task and in a number of studies is solved by including the method of developing mathematical models and creating on their basis the appropriate optimal schemes for building these systems. The final stage of development and implementation of such mathematical models

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Xu, Shaoshan, Jun Shen, Haochen Hua, et al. "Trading Portfolio Strategy Optimization via Mean-Variance Model Considering Multiple Energy Derivatives." Processes 11, no. 2 (2023): 532. http://dx.doi.org/10.3390/pr11020532.

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Energy retailers that sell energy at fixed prices are at risk of bankruptcy due to instantaneous fluctuations in wholesale electricity prices. Energy derivatives, e.g., electricity options, can be purchased by energy retailers then sold to customers as one potential risk-mitigation tool. A class of energy retailers that trade energy derivatives, including the electricity option, the carbon option and the green certificate, is considered in this paper. In terms of energy retailers, a strategy that can maximize the value of the purchased energy derivatives over a period of time and minimize the

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Mandallaz, Daniel, and Ronghua Ye. "Forest inventory with optimal two-phase two-stage sampling schemes based on the anticipated variance." Canadian Journal of Forest Research 29, no. 11 (1999): 1691–708. http://dx.doi.org/10.1139/x99-124.

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This work presents optimal sampling schemes for forest inventory. The sampling procedures are optimal in the sense that they minimize the anticipated variance for given costs or conversely, the anticipated variance is the average of the design-based variance under a local Poisson model for the spatial distribution of the trees. The resulting optimal inclusion rules are either probability proportional to size, in one-stage procedures, or a combination of probability proportional to prediction and probability proportional to error, in two-stage procedures. Best feasible approximations of the exa

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Solomon, Joshua A., and Christopher W. Tyler. "A Brücke–Bartley effect for contrast." Royal Society Open Science 5, no. 8 (2018): 180171. http://dx.doi.org/10.1098/rsos.180171.

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Accurate derivation of the psychophysical (a.k.a. transducer) function from just-notable differences requires accurate knowledge of the relationship between the mean and variance of apparent intensities. Alternatively, a psychophysical function can be derived from estimates of the average between easily discriminable intensities. Such estimates are unlikely to be biased by the aforementioned variance, but they are notoriously variable and may stem from decisional processes that are more cognitive than sensory. In this paper, to minimize cognitive pollution, we used amplitude-modulated contrast

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Azcue, Pablo, Xiaoqing Liang, Nora Muler, and Virginia R. Young. "Optimal Reinsurance to Minimize the Probability of Drawdown under the Mean-Variance Premium Principle: Asymptotic Analysis." SIAM Journal on Financial Mathematics 14, no. 1 (2023): 279–313. http://dx.doi.org/10.1137/21m1461666.

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Brecht, M. L., J. Arthur Woodward, and Jodi Gistenson. "Comparison of Three Statistical Computer Programs in Teaching Analysis of Variance." Journal of Educational Technology Systems 13, no. 4 (1985): 237–47. http://dx.doi.org/10.2190/jldj-0lpc-7lfd-j00x.

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Subjects analyzed data from typical ANOVA designs using three different computer programs. Several measures of cost, completion, and ease of program use were recorded and compared in a repeated measures Latin square design. Within time constraints and support that simulate an instructional setting, subjects could not answer the research questions using two traditional computer packages, but subjects completed all analyses using an interactive personal computer program designed to minimize computer-related difficulties. Such results can be useful in guiding design of instructional strategies an

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de Maeyer, Rieke, Sami Sieranoja, and Pasi Fränti. "Balanced k-means revisited." Applied Computing and Intelligence 3, no. 2 (2023): 145–79. http://dx.doi.org/10.3934/aci.2023008.

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<abstract><p>The $ k $-means algorithm aims at minimizing the variance within clusters without considering the balance of cluster sizes. Balanced $ k $-means defines the partition as a pairing problem that enforces the cluster sizes to be strictly balanced, but the resulting algorithm is impractically slow $ \mathcal{O}(n^3) $. Regularized $ k $-means addresses the problem using a regularization term including a balance parameter. It works reasonably well when the balance of the cluster sizes is a mandatory requirement but does not generalize well for soft balance requirements. In

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Ratsimbanierana, Hermann, Sara Sbai, and Agathe Stenger. "Moroccan tourist portfolio efficiency with the mean-variance approach." European Journal of Tourism Research 6, no. 2 (2013): 122–31. http://dx.doi.org/10.54055/ejtr.v6i2.126.

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Nowadays, the major objective of all destinations is the development. Develop their attractions, their management strategy to cope with the competition and attract the maximum number of tourists, satisfy and retain them. This paper analyses the Moroccan destination performance with the use of the mean-variance shortage function approach. This method permits to help destination decision- makers to minimize the instability and maximize the return of inbound tourism. Accordingly, to optimize its tourism strategy, the Moroccan tourism authority can choose a combination of tourist origins according

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Chen, Chun, Zhengguang Chen, Jiajun Bu, Can Wang, Lijun Zhang, and Cheng Zhang. "G-Optimal Design with Laplacian Regularization." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (2010): 413–18. http://dx.doi.org/10.1609/aaai.v24i1.7672.

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In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attempts to discover the most informative data points for labeling. Recently, Optimal Experimental Design (OED) techniques have attracted an increasing amount of attention. OED is concerned with the design of experiments that minimizes variances of a parameterized model. Typical design criteria include D-, A-, and E-optimality. However, all these criteria are based on an ordinary linear regression model which aims to minim

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Abdallah, Muhammad Naif, Werry Febrianti, and Lutfi Mardianto. "Optimasi Portofolio Berdasarkan Model Mean-Variance dengan menggunakan Lagrange Multiplier pada saham IDX30." Indonesian Journal of Applied Mathematics 4, no. 2 (2025): 38. https://doi.org/10.35472/indojam.v4i2.1983.

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This study aims to optimize the portofolio of stocks included in the IDX30 index using the Mean-Variance model developed by Markowitz. The Lagrange Multiplier method is used in this study to determine the optimal fund allocation by minimizing risk and optimizing expected return. The data used is the daily closing price of stocks from 15 companies listed in the IDX30 index over the last five years (2019-2024). The results show that the Mean-Variance and Lagrange Multiplier methods are effective in identifying the optimal portofolio that can minimize investment risk while maximizing returns

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