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Journal articles on the topic 'Range estimating'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 February 2022

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1

De Haan, L., and Sidney Resnick. "Estimating the home range." Journal of Applied Probability 31, no. 3 (September 1994): 700–720. http://dx.doi.org/10.2307/3215149.

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A proposal is given for estimating the home range of an animal based on sequential sightings. We assume the given sightings are independent, identically distributed random vectors X1,· ··, Xn whose common distribution has compact support. If are the polar coordinates of the sightings, then is a sup-measure and corresponds to the right endpoint of the distribution . The corresponding upper semi-continuous function l(θ) is the boundary of the home range. We give a consistent estimator for the boundary l and under the assumption that the distribution of R1 given is in the domain of attraction of an extreme value distribution with bounded support, we are able to give an approximate confidence region.

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2

Dallas, Tad, Shan Huang, Charles Nunn, Andrew W. Park, and John M. Drake. "Estimating parasite host range." Proceedings of the Royal Society B: Biological Sciences 284, no. 1861 (August 30, 2017): 20171250. http://dx.doi.org/10.1098/rspb.2017.1250.

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Estimating the number of host species that a parasite can infect (i.e. host range) provides key insights into the evolution of host specialism and is a central concept in disease ecology. Host range is rarely estimated in real systems, however, because variation in species relative abundance and the detection of rare species makes it challenging to confidently estimate host range. We applied a non-parametric richness indicator to estimate host range in simulated and empirical data, allowing us to assess the influence of sampling heterogeneity and data completeness. After validating our method on simulated data, we estimated parasite host range for a sparsely sampled global parasite occurrence database (Global Mammal Parasite Database) and a repeatedly sampled set of parasites of small mammals from New Mexico (Sevilleta Long Term Ecological Research Program). Estimation accuracy varied strongly with parasite taxonomy, number of parasite occurrence records, and the shape of host species-abundance distribution (i.e. the dominance and rareness of species in the host community). Our findings suggest that between 20% and 40% of parasite host ranges are currently unknown, highlighting a major gap in our understanding of parasite specificity, host–parasite network structure, and parasite burdens.

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3

Su, C. C., A. Bovik, and L. Cormack. "ESTIMATING RANGE FROM LUMINANCE." Journal of Vision 12, no. 9 (August 10, 2012): 278. http://dx.doi.org/10.1167/12.9.278.

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4

De Haan, L., and Sidney Resnick. "Estimating the home range." Journal of Applied Probability 31, no. 03 (September 1994): 700–720. http://dx.doi.org/10.1017/s0021900200045277.

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A proposal is given for estimating the home range of an animal based on sequential sightings. We assume the given sightings are independent, identically distributed random vectors X 1,· ··, Xn whose common distribution has compact support. If are the polar coordinates of the sightings, then is a sup-measure and corresponds to the right endpoint of the distribution . The corresponding upper semi-continuous function l(θ) is the boundary of the home range. We give a consistent estimator for the boundary l and under the assumption that the distribution of R 1 given is in the domain of attraction of an extreme value distribution with bounded support, we are able to give an approximate confidence region.

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5

Lipman, Harvey B., and J. Rex Astles. "Estimating the linear analytic range." Clinica Chimica Acta 282, no. 1-2 (April 1999): 15–34. http://dx.doi.org/10.1016/s0009-8981(98)00219-8.

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6

Fox, N. I., and C. G. Collier. "Estimating medium-range catchment flood potential." Journal of Hydrology 237, no. 1-2 (October 2000): 1–16. http://dx.doi.org/10.1016/s0022-1694(00)00285-7.

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7

Merz, A. W. "Estimating retrosensor position from range data." Journal of Guidance, Control, and Dynamics 14, no. 5 (September 1991): 1071–72. http://dx.doi.org/10.2514/3.20755.

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8

Zhao, Xiaofeng, Caglar Yardim, Dongxiao Wang, and Bruce M. Howe. "Estimating Range-Dependent Evaporation Duct Height." Journal of Atmospheric and Oceanic Technology 34, no. 5 (May 2017): 1113–23. http://dx.doi.org/10.1175/jtech-d-16-0125.1.

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AbstractThe refractivity from clutter (RFC) technique has been proved to be an effective way to estimate atmospheric duct structure. An important issue for RFC is how to make the estimate more robust, especially in range-dependent ducting conditions. Traditionally, statistical inversion methods need a large number of forward propagation model runs to obtain an acceptable result. Especially when the parameter search space is multidimensional, these methods are prone to being trapped into local optimal solutions. Recently published results (Zhao and Huang) indicate that the adjoint parabolic equation (PE) method holds promise for real-time estimation of one-dimensional refractive index structure from radar sea clutter returns. This paper is aimed at extending the adjoint PE method to range-dependent evaporation duct cases, with a log-linear relationship describing duct structures. Numerical simulations are used to test the performance of this method and the results are compared with that retrieved using a genetic algorithm. Both noise-free and 3-dB additive Gaussian noise clutter simulations are considered, as well as linearly and nonlinearly varying duct height with range.

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9

Shaheen, Ahmed A., Aminah Robinson Fayek, and S. M. AbouRizk. "Fuzzy Numbers in Cost Range Estimating." Journal of Construction Engineering and Management 133, no. 4 (April 2007): 325–34. http://dx.doi.org/10.1061/(asce)0733-9364(2007)133:4(325).

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10

Fredlund, Delwyn G., Daichao Sheng, and Jidong Zhao. "Estimation of soil suction from the soil-water characteristic curve." Canadian Geotechnical Journal 48, no. 2 (February 2011): 186–98. http://dx.doi.org/10.1139/t10-060.

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Soil-water characteristic curves (SWCCs) are routinely used for the estimation of unsaturated soil property functions (e.g., permeability functions, water storage functions, shear strength functions, and thermal property functions). This paper examines the possibility of using the SWCC for the estimation of in situ soil suction. The paper focuses on the limitations of estimating soil suctions from the SWCC and also suggests a context under which soil suction estimations should be used. The potential range of estimated suction values is known to be large because of hysteresis between drying and wetting SWCCs. For this, and other reasons, the estimation of in situ suctions from the SWCC has been discouraged. However, a framework is suggested in this paper for estimating the median value for in situ soil suction along with a likely range of soil suction values (i.e., maximum and minimum values). The percentage error in the estimation of soil suction from the SWCC is shown to be lowest for sand soils and highest for clay soils.

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11

Dai, Tianlu, Boya Zhou, Yanyi Zhang, Guang Chen, and Peng Liu. "Rapid Evaluation Method for Accuracy of Range Estimation of Pure Electric Vehicle Range Estimation Based on CLTC-P." E3S Web of Conferences 235 (2021): 01035. http://dx.doi.org/10.1051/e3sconf/202123501035.

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Based on theoretical and experimental research, this paper constructs a rapid test method for estimating the accuracy of the range of pure electric vehicles based on CLTC-P, which is based on different environmental temperatures, air conditioning use, test scenarios, and high-speed operating conditions. The article further compares and analyzes a variety of mathematical statistical methods and selects certain coefficients to evaluate the accuracy of cruising range estimation, and proposes a general rapid test method and evaluation theory of cruising range estimation accuracy, which lays the foundation for establishing a unified assessment standard in industry, and promotes the development of the electric vehicle industry.

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12

Liderman, Krzysztof. "Risk of undesired changes to significant information quality criteria." Przegląd Teleinformatyczny 7(25), no. 3-4 (December 20, 2019): 31–55. http://dx.doi.org/10.5604/01.3001.0013.6597.

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The article presents a method of estimating the risk of an undesirable change in the information quality criterion of secrecy, meaning estimating the risk of a certain class of information security incidents. The qualitative risk estimation method is adopted and the impact of a descriptive grade composition method on the results is discussed. The paper also shows considerations on the possibilities of interpreting the variables used in risk estimation and establishing the range of their actual values. It also describes how the identified range of actual variable values translates into grades used in risk estimation.

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13

Stone, Paul A., and Troy A. Baird. "Estimating Lizard Home Range: The Rose Model Revisited." Journal of Herpetology 36, no. 3 (September 2002): 427–36. http://dx.doi.org/10.1670/0022-1511(2002)036[0427:elhrtr]2.0.co;2.

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14

Du, Chang Qing, Gang Du, Ke Cheng Tan, and Yong Shan Liu. "Research on Remaining Driving Range Estimation of Electric Vehicle Based on Dynamic Working Condition." Advanced Materials Research 945-949 (June 2014): 509–15. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.509.

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Aimed at estimating the remaining driving range of electric vehicle (EV) on dynamic working condition and exploring the influences on remaining driving range estimation, combined GT-Drive and Matlab, EV simulation model and remaining driving range estimation model have established. Based on UDDS, compared simulation results with estimation results of remaining driving range, the influences on remaining driving range estimation have been discovered, then a optimization scheme is put forward. With the method of corrected parameter, the error of initial estimation value is reduced; when braking energy recovery module is added, EV simulation model is optimized. The results of test indicates that the optimized model has realized to accurately estimate the remaining driving range, meets the requirements of the expected estimation accuracy.

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15

Vierinen, J. "Fractional baud-length coding." Annales Geophysicae 29, no. 6 (June 30, 2011): 1189–96. http://dx.doi.org/10.5194/angeo-29-1189-2011.

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Abstract. We present a novel approach for modulating radar transmissions in order to improve target range and Doppler estimation accuracy. This is achieved by using non-uniform baud lengths. With this method it is possible to increase sub-baud range-resolution of phase coded radar measurements while maintaining a narrow transmission bandwidth. We first derive target backscatter amplitude estimation error covariance matrix for arbitrary targets when estimating backscatter in amplitude domain. We define target optimality and discuss different search strategies that can be used to find well performing transmission envelopes. We give several simulated examples of the method showing that fractional baud-length coding results in smaller estimation errors than conventional uniform baud length transmission codes when estimating the target backscatter amplitude at sub-baud range resolution. We also demonstrate the method in practice by analyzing the range resolved power of a low-altitude meteor trail echo that was measured using a fractional baud-length experiment with the EISCAT UHF system.

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16

Wang, Yongbing, Wen-Qin Wang, and Huaizong Shao. "Frequency Diverse Array Radar Cramér-Rao Lower Bounds for Estimating Direction, Range, and Velocity." International Journal of Antennas and Propagation 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/830869.

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Different from phased-array radar, frequency diverse array (FDA) radar offers range-dependent beampattern and thus provides new application potentials. But there is a fundamental question: what estimation performance can achieve for an FDA radar? In this paper, we derive FDA radar Cramér-Rao lower bounds (CRLBs) for estimating direction, range (time delay), and velocity (Doppler shift). Two different data models including pre- and postmatched filtering are investigated separately. As the FDA radar has range-angle coupling, we use a simple transmit subaperturing strategy which divides the whole array into two subarrays, each uses a distinct frequency increment. Assuming temporally white Gaussian noise and linear frequency modulated transmit signal, extensive simulation examples are performed. When compared to conventional phased-array radar, FDA can yield better CRLBs for estimating the direction, range, and velocity. Moreover, the impacts of the element number and frequency increment are also analyzed. Simulation results show that the CRLBs decrease with the increase of the elements number and frequency increment.

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17

Yildiz, A. "Estimating the full range of thermal conductivity dryout curve." Géotechnique Letters 10, no. 3 (September 2020): 419–23. http://dx.doi.org/10.1680/jgele.20.00055.

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18

Vikić-Topić, D., and Z. Meić. "CF long range coupling for estimating molecular conformations." Journal of Molecular Structure 142 (March 1986): 371–74. http://dx.doi.org/10.1016/0022-2860(86)85136-5.

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19

Nizami, Lance. "Estimating auditory neuronal dynamic range using a fitted function." Hearing Research 167, no. 1-2 (May 2002): 13–27. http://dx.doi.org/10.1016/s0378-5955(02)00293-9.

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20

Krbálek, Milan, Jiří Apeltauer, Tomáš Apeltauer, and Zuzana Szabová. "Three methods for estimating a range of vehicular interactions." Physica A: Statistical Mechanics and its Applications 491 (February 2018): 112–26. http://dx.doi.org/10.1016/j.physa.2017.09.008.

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21

Utsunomiya, Akane, Junji Shiraishi, Hiroko Ueda, and Nobuko Hanaoka. "ROC analysis for estimating optimal density range of radiography." Japanese Journal of Radiological Technology 52, no. 9 (1996): 1246. http://dx.doi.org/10.6009/jjrt.kj00001354988.

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22

Pearce, Annie R., Rita A. Gregory, and Laura Williams. "Range Estimating for Risk Management Using Artificial Neural Networks." Journal of Parametrics 19, no. 1 (March 1999): 3–31. http://dx.doi.org/10.1080/10157891.1999.10462578.

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23

Kuznetsov, A. V. "Estimating the measurement range of a monochromatic television pyrometer." Journal of Optical Technology 75, no. 1 (January 1, 2008): 30. http://dx.doi.org/10.1364/jot.75.000030.

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24

Huang, Wei-qiong, and Xuan Wu. "Influence of statistical time range on estimating seismicity parameters." Acta Seismologica Sinica 14, no. 6 (November 2001): 626–33. http://dx.doi.org/10.1007/bf02718073.

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25

Calabrese, Edward J., Evgenios Agathokleous, Walter J. Kozumbo, Edward J. Stanek, and Denise Leonard. "Estimating the range of the maximum hormetic stimulatory response." Environmental Research 170 (March 2019): 337–43. http://dx.doi.org/10.1016/j.envres.2018.12.020.

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26

Costa, Yuri A., Carlos P. Filho, Gabriela A. Flores, Evandro L. L. Rodrigues, and Fernando F. Paiva. "Full-Range Liver Fat Fraction Estimation in Magnitude MRI Using a Signal Shape Descriptor." Concepts in Magnetic Resonance Part A 2019 (July 9, 2019): 1–11. http://dx.doi.org/10.1155/2019/3439468.

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Current methods for estimation of proton density fat fraction (PDFF) of the liver using magnitude magnetic resonance (MR) imaging face the challenge of correctly estimating it when fat is the dominant molecule; i.e., PDFF is more than 50%. Therefore, the accuracy of the methods is limited to half-range operation. We introduce a method based on neural networks for regression capable of estimating over the full range of fat fractions. We built a neural network based on the angles and distances between the data in the discrete MR signal (ADALIFE), using these as features associated with different PDFFs and as input for the network. Tests were performed using ADALIFE and Multi-interference, a state-of-the-art method to estimate PDFFs, with simulated signals at various signal-to-noise (SNR) values. Results were compared in order to verify repeatability and agreement using Bland-Altman and REC curves. Results for Multi-interference were similar to its in vivo literature, showing the relevance of a simulation. ADALIFE was able to correctly estimate fat fractions up to 100%, breaking the current paradigm for full-range estimation using only offline postprocessing. Within half range, our method outperformed Multi-interference in repeatability and agreement, with narrower limits of agreement and lower expected error at any SNR.

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27

Wang, Zhanshan, Longhu Quan, and Xiuchong Liu. "Sensorless SPMSM Position Estimation Using Position Estimation Error Suppression Control and EKF in Wide Speed Range." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/480640.

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The control of a high performance alternative current (AC) motor drive under sensorless operation needs the accurate estimation of rotor position. In this paper, one method of accurately estimating rotor position by using both motor complex number model based position estimation and position estimation error suppression proportion integral (PI) controller is proposed for the sensorless control of the surface permanent magnet synchronous motor (SPMSM). In order to guarantee the accuracy of rotor position estimation in the flux-weakening region, one scheme of identifying the permanent magnet flux of SPMSM by extended Kalman filter (EKF) is also proposed, which formed the effective combination method to realize the sensorless control of SPMSM with high accuracy. The simulation results demonstrated the validity and feasibility of the proposed position/speed estimation system.

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28

Jemitola, P. O., G. Monterzino, and J. Fielding. "Wing mass estimation algorithm for medium range box wing aircraft." Aeronautical Journal 117, no. 1189 (March 2013): 329–40. http://dx.doi.org/10.1017/s0001924000008022.

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Abstract A procedure for defining an empirical formula for the mass estimation of the fore and aft wings field Uof a medium range box wing aircraft is described. The procedure is based upon the work of Howe for estimating the wing mass of conventional cantilever wing aircraft. The paper outlines the procedure used to relate conventional cantilever wings to box wing aircraft wings. Using a vortex lattice tool, finite element methods and regression analysis, the modification performed on the coefficient in Howe’s method to enable its use on a medium range box wing aircraft is outlined. The results show that the fore and aft wings would use the same correction coefficient and that the aft wing would therefore be lighter than the fore wing on a medium range box wing aircraft.

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29

Yao, En Jian, Zhi Qiang Yang, Hong Na Dai, and Ting Zuo. "Estimation of Electric Vehicle's Crusing Range Based on Real-Time Links Average Speed." Applied Mechanics and Materials 361-363 (August 2013): 2100–2103. http://dx.doi.org/10.4028/www.scientific.net/amm.361-363.2100.

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For the reasons of relative short cruising range and insufficient charging facilities, the use and promotion of electric vehicles (EV) is restricted. The estimation of cruising range is important for the EV drivers when selecting the travel route. Energy consumption for different running status is the prerequisite for estimation of cruising range. In this study, an energy consumption factor model is established, which is characterized with reflecting the impact of frequent acceleration and deceleration of urban road, and the input parameter is easily obtained from usual road traffic information system. The results show that the proposed model can predict energy consumption with high accuracy. Then based on real-time links average travel speed, this paper proposes a method of estimating the cruising range when EV travels on a planned route according to drivers demand.

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30

Yao, En Jian, Mei Ying Wang, Yuan Yuan Song, and Ting Zuo. "Estimating the Cruising Range of Electric Vehicle Based on Instantaneous Speed and Acceleration." Applied Mechanics and Materials 361-363 (August 2013): 2104–8. http://dx.doi.org/10.4028/www.scientific.net/amm.361-363.2104.

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In contrast to fuel vehicles, the wide-spread use of electric vehicles (EVs) is still hindered by limited battery capacity and cruising range. It is important to forecast the EVs cruising range accurately before departure and reduce the risk of running out of electricity before arriving at the destination or charging station. In this article, through analyzing the variation characteristics of energy consumption rate with instantaneous speed and acceleration, a series of EV energy consumption rate models are established according to different operation modes. Further, a novel cruising range estimation method is proposed based on the presented EV energy consumption rate models, which is characterized by fully considering the impacts of instantaneous speed and acceleration. Finally, using the simulation data of a road in Beijing, the model presented in this article is utilized in conjunction with microscopic traffic simulation technologies to demonstrate its application in estimating the EVs cruising range under different traffic volumes.

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31

Vens, M., and A. Ziegler. "Generalized Estimating Equations." Methods of Information in Medicine 49, no. 05 (2010): 421–25. http://dx.doi.org/10.3414/me10-01-0026.

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Summary Background: Generalized estimating equations (GEE) are an extension of generalized linear models (GLM) in that they allow adjusting for correlations between observations. A major strength of GEE is that they do not require the correct specification of the multivariate distribution but only of the mean structure. Objectives: Several concerns have been raised about the validity of GEE when applied to dichotomous dependent variables. In this contribution, we summarize the theoretical findings concerning efficiency and validity of GEE. Methods: We introduce the GEE in a formal way, summarize general findings on the choice of the working correlation matrix, and show the existence of a dilemma for the optimal choice of the working correlation matrix for dichotomous dependent variables. Results: Biological and statistical arguments for choosing a specific working correlation matrix are given. Three approaches are described for overcoming the range restriction of the correlation coefficient. Conclusions: The three approaches described in this article for overcoming the range restrictions for dichotomous dependent variables in GEE models provide a simple and practical way for use in applications.

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32

박종해. "Forecasting Power of Range Volatility According to Different Estimating Period." Management & Information Systems Review 30, no. 2 (June 2011): 237–55. http://dx.doi.org/10.29214/damis.2011.30.2.010.

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33

Ruokolainen, Kalle, Hanna Tuomisto, Jaana Vormisto, and Nigel Pitman. "Two biases in estimating range sizes of Amazonian plant species." Journal of Tropical Ecology 18, no. 6 (September 25, 2002): 935–42. http://dx.doi.org/10.1017/s0266467402002614.

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The Amazonian rain forests form one of the largest areas of continuous forest in the world, and they harbour a substantial part of the world's biodiversity (World Conservation Monitoring Centre 1992). The extravagant species richness of Amazonia makes collecting information on species distribution patterns there a formidable challenge. Relatively few studies have been able to provide data that cover both a large enough number of species and wide enough geographical areas to allow relevant biogeographical and ecological generalizations (such studies concerning plants include Balslev 1988, de Oliveira & Daly 1999, Pitman et al. 1999, Prance 1973, ter Steege et al. 2000, Terborgh & Andresen 1998, Tuomisto & Poulsen 1996). The scarcity of field observations is undoubtedly one of the reasons why very different ideas exist about the mechanisms that control plant distributions and patterns of species richness in Amazonia (Balslev 1988, Condit 1996, Gentry 1988, Nelson et al 1990, Pitman et al. 1999, Prance 1973, 1982; ter Steege et al. 2000, Tuomisto et al. 1995).

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34

Ceraolo, M., and G. Pede. "Techniques for estimating the residual range of an electric vehicle." IEEE Transactions on Vehicular Technology 50, no. 1 (2001): 109–15. http://dx.doi.org/10.1109/25.917893.

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35

Cabral, Juliano S., and Frank M. Schurr. "Estimating demographic models for the range dynamics of plant species." Global Ecology and Biogeography 19, no. 1 (September 30, 2009): 85–97. http://dx.doi.org/10.1111/j.1466-8238.2009.00492.x.

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36

Mount, John A. "Estimating the range of a function in an online setting." Information Processing Letters 72, no. 1-2 (October 1999): 31–35. http://dx.doi.org/10.1016/s0020-0190(99)00118-0.

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37

Weron, Rafał. "Estimating long-range dependence: finite sample properties and confidence intervals." Physica A: Statistical Mechanics and its Applications 312, no. 1-2 (September 2002): 285–99. http://dx.doi.org/10.1016/s0378-4371(02)00961-5.

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38

Baker, JD, AL Harting, TC Johanos, and CL Littnan. "Estimating Hawaiian monk seal range-wide abundance and associated uncertainty." Endangered Species Research 31 (December 6, 2016): 317–24. http://dx.doi.org/10.3354/esr00782.

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39

Kuc, Roman. "Neuromorphic Processing of Moving Sonar Data for Estimating Passing Range." IEEE Sensors Journal 7, no. 5 (May 2007): 851–59. http://dx.doi.org/10.1109/jsen.2007.894138.

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40

Peterson, David L., and Michael J. Arbaugh. "Estimating postfire survival of Douglas-fir in the Cascade Range." Canadian Journal of Forest Research 19, no. 4 (April 1, 1989): 530–33. http://dx.doi.org/10.1139/x89-084.

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Factors related to survival of Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco) 2 years after spring wildfires were evaluated at four sites in the Cascade Range. A logistic regression model was developed to estimate postfire survival. Crown scorch and three variables related to bole damage were significant in the regression model, with differences in response among sites attributed to differences in size class. The regression model predicted postfire response of live trees more accurately than that of dead trees, based on estimates of survival probability. Crown scorch was the most significant predictor of tree response, although the importance of additional variables indicated that evaluating bole damage greatly improves postfire survival estimates.

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41

Wu, Yuntao, Yi Dong, and Guisheng Liao. "Jointly estimating both range and DOA of near field source." Journal of Electronics (China) 21, no. 2 (March 2004): 104–9. http://dx.doi.org/10.1007/bf02687824.

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42

Ostro, Linde E. T., Truman P. Young, Scott C. Silver, and Fred W. Koontz. "A Geographic Information System Method for Estimating Home Range Size." Journal of Wildlife Management 63, no. 2 (April 1999): 748. http://dx.doi.org/10.2307/3802665.

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43

Monterroso, Pedro, Neftalí Sillero, Luís Miguel Rosalino, Filipa Loureiro, and Paulo Célio Alves. "Estimating home-range size: when to include a third dimension?" Ecology and Evolution 3, no. 7 (June 8, 2013): 2285–95. http://dx.doi.org/10.1002/ece3.590.

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44

Rychtář, Jan, and Dewey T. Taylor. "Estimating the sample variance from the sample size and range." Statistics in Medicine 39, no. 30 (September 15, 2020): 4667–86. http://dx.doi.org/10.1002/sim.8747.

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45

Zheng, Xiaogu, and James Renwick. "Estimating interannual variability arising from weather events." Journal of Applied Probability 38, A (2001): 274–88. http://dx.doi.org/10.1017/s0021900200112859.

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The advantages and limitations of frequency domain and time domain methods for estimating the interannual variability arising from day-to-day weather events are summarized. A modification of the time domain method is developed and its application in examining a precondition for the frequency domain method is demonstrated. A combined estimation procedure is proposed: it takes advantage of the strengths of both methods. The estimation procedures are tested with sets of synthetic data and are applied to long time series of three meteorological parameters. The impacts of the different methods on tests of potential long-range predictability for seasonal means are also discussed.

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Zheng, Xiaogu, and James Renwick. "Estimating interannual variability arising from weather events." Journal of Applied Probability 38, A (2001): 274–88. http://dx.doi.org/10.1239/jap/1085496609.

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The advantages and limitations of frequency domain and time domain methods for estimating the interannual variability arising from day-to-day weather events are summarized. A modification of the time domain method is developed and its application in examining a precondition for the frequency domain method is demonstrated. A combined estimation procedure is proposed: it takes advantage of the strengths of both methods. The estimation procedures are tested with sets of synthetic data and are applied to long time series of three meteorological parameters. The impacts of the different methods on tests of potential long-range predictability for seasonal means are also discussed.

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Rodríguez-García, Marco A., Isaac Pérez Castillo, and P. Barberis-Blostein. "Efficient qubit phase estimation using adaptive measurements." Quantum 5 (June 4, 2021): 467. http://dx.doi.org/10.22331/q-2021-06-04-467.

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Estimating correctly the quantum phase of a physical system is a central problem in quantum parameter estimation theory due to its wide range of applications from quantum metrology to cryptography. Ideally, the optimal quantum estimator is given by the so-called quantum Cramér-Rao bound, so any measurement strategy aims to obtain estimations as close as possible to it. However, more often than not, the current state-of-the-art methods to estimate quantum phases fail to reach this bound as they rely on maximum likelihood estimators of non-identifiable likelihood functions. In this work we thoroughly review various schemes for estimating the phase of a qubit, identifying the underlying problem which prohibits these methods to reach the quantum Cramér-Rao bound, and propose a new adaptive scheme based on covariant measurements to circumvent this problem. Our findings are carefully checked by Monte Carlo simulations, showing that the method we propose is both mathematically and experimentally more realistic and more efficient than the methods currently available.

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Rechenauer, Tobias, Jakob Zierk, Daniel Gräfe, Wolfgang Rascher, Manfred Rauh, and Markus Metzler. "A Comparison of GFR Estimation Formulae in Pediatric Oncology." Klinische Pädiatrie 230, no. 03 (April 9, 2018): 142–50. http://dx.doi.org/10.1055/a-0587-5753.

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Abstract Background Application of potentially nephrotoxic chemotherapy requires continuous monitoring of renal function for toxicity and dosing. Novel pediatric glomerular filtration rate (GFR) estimating equations including cystatin C have been proposed to enhance the reliability of GFR calculation. Materials and methods We examined a pediatric oncologic data set with a total of 363 GFR measurements. An analysis of distribution characteristics and comparison of medians was performed to compare creatinine and cystatin C-based GFR estimating formulae. Furthermore, we investigated the clinical impact of different equations in regard to therapeutic consequences. Results Significant differences in estimated GFR values were calculated depending on the applied formula (range of median GFR from 94.8 to 180.9 mL/min per 1.73 m2) which may result in different therapeutic consequences for the use of potentially nephrotoxic chemotherapeutic agents. Significant correlation for all examined formulae was identified, however there were large fluctuations among the correlation coefficients ranging from 0.254 to 1.0. Conclusion This study compares proposed pediatric GFR estimating equations in a clinical setting. It underlines the current limitations and difficulties of GFR estimation including potential dosing errors. Cystitis C-based equations can be used as alternatives to creatinine-based estimations when the appropriate laboratory method has been applied. A comparative calculator for pediatric GFR estimating equations along with background information is provided at http://gfr.pedz.de and may support clinical decision-making.

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Chen, Wei, Ruisheng Sun, and Weisheng Yan. "Optimal Position and Velocity Estimation for Multi-USV Positioning Systems with Range Measurements." Complexity 2018 (July 10, 2018): 1–12. http://dx.doi.org/10.1155/2018/5452723.

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This paper investigates the problem on simultaneously estimating the velocity and position of the target for range-based multi-USV positioning systems. According to the range measurement and kinematics model of the target, we formulate this problem in a mixed linear/nonlinear discrete-time system. In this system, the input and state represent the velocity and position of the target, respectively. We divide the system into two components and propose a three-step minimum variance unbiased simultaneous input and state estimation (SISE) algorithm. First, we estimate the velocity in the local level plane and predict the corresponding position. Then, we estimate the velocity in the heave direction. Finally, we estimate the 3-dimensional (3D) velocity and position. We establish the unbiased conditions of the input and state estimation for the MLBL system. Simulation results illustrate the effectiveness of the problem formulation and demonstrate the performance of the proposed algorithm.

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GHOSH, S., A. K. ROY, and S. MUKHERJEE. "LONG-RANGE POTENTIAL AND TWO GLUINO BOUND STATES." Modern Physics Letters A 02, no. 03 (March 1987): 183–91. http://dx.doi.org/10.1142/s0217732387000240.

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The effect of the long-range confining potential on the two gluino bound states has been studied in a particular potential model. Some useful inequalities for the value of the wave function at the origin, [Formula: see text] have been derived for a more general class of potentials. The results will be useful for estimating various decay widths.

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