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Journal articles on the topic 'Characteristic of probability'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 May 2022

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1

Uehara, Erica, and Tetsuo Deguchi. "Characteristic length of the knotting probability revisited." Journal of Physics: Condensed Matter 27, no. 35 (August 20, 2015): 354104. http://dx.doi.org/10.1088/0953-8984/27/35/354104.

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2

Chern, Jyh-Long, and Timothy Chi Chow. "Nonstationary characteristic of probability association in chaos." Physics Letters A 192, no. 1 (August 1994): 34–42. http://dx.doi.org/10.1016/0375-9601(94)91011-1.

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3

Meintanis, Simos G., and Nikolai G. Ushakov. "Nonparametric probability weighted empirical characteristic function and applications." Statistics & Probability Letters 108 (January 2016): 52–61. http://dx.doi.org/10.1016/j.spl.2015.08.021.

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4

Lehnigk, Siegfried H. "Characteristic functions of a class of probability distributions." Complex Variables, Theory and Application: An International Journal 8, no. 3-4 (June 1987): 307–32. http://dx.doi.org/10.1080/17476938708814241.

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5

DEL RIO, EZEQUIEL, and SERGIO ELASKAR. "NEW CHARACTERISTIC RELATIONS IN TYPE-II INTERMITTENCY." International Journal of Bifurcation and Chaos 20, no. 04 (April 2010): 1185–91. http://dx.doi.org/10.1142/s0218127410026381.

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We study analytically and numerically the reinjection probability density for type-II intermittency. We find a new one-parameter class of reinjection probability density where the classical uniform reinjection is a particular case. We derive a new duration probability density of the laminar phase. New characteristic relations eβ(-1 < β < 0) appear where the exponet β deepens on the reinjection probability distributions. Analytical results are in agreement with the numerical simulations.

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6

Piegari, E., R. Di Maio, and L. Milano. "Characteristic scales in landslide modelling." Nonlinear Processes in Geophysics 16, no. 4 (July 22, 2009): 515–23. http://dx.doi.org/10.5194/npg-16-515-2009.

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Abstract. Landslides are natural hazards occurring in response to triggers of different origins, which can act with different intensities and durations. Despite the variety of conditions that cause a landslide, the analysis of landslide inventories has shown that landslide events associated with different triggers can be characterized by the same probability distribution. We studied a cellular automaton, able to reproduce the landslide frequency-size distributions from catalogues. From the comparison between our synthetic probability distribution and the landslide area probability distribution of three landslide inventories, we estimated the typical size of a single cell of our cellular automaton model to be from 35–100 m2, which is important information if we are interested in monitoring a test area. To determine the probability of occurrence of a landslide of size s, we show that it is crucial to get information about the rate at which the system is approaching instability rather than the nature of the trigger. By varying such a driving rate, we find how the probability distribution changes and, in correspondence, how the size and the lifetime of the most probable events evolve. We also introduce a landslide-event magnitude scale based on the driving rate. Large values of the proposed intensity scale are related to landslide events with a fast approach to instability in a long distance of time, while small values are related to landslide events close together in time and approaching instability slowly.

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7

Norvidas, Saulius. "On analytic continuation of characteristic functions of probability measures." Journal of Mathematical Analysis and Applications 390, no. 1 (June 2012): 93–98. http://dx.doi.org/10.1016/j.jmaa.2012.01.020.

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8

Yan, GU. "Quantum statistical mechanics, quantum probability and quantum characteristic function." SCIENTIA SINICA Physica, Mechanica & Astronomica 50, no. 7 (April 20, 2020): 070002. http://dx.doi.org/10.1360/sspma-2019-0365.

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9

Wu, Jia, Genghua Yu, and Peiyuan Guan. "Interest Characteristic Probability Predicted Method in Social Opportunistic Networks." IEEE Access 7 (2019): 59002–12. http://dx.doi.org/10.1109/access.2019.2915359.

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10

Gapeev, M. I., Yu I. Senkevich, and O. O. Lukovenkova. "Estimation of Probability Distributions of Geoacoustic Signal Characteristics." Journal of Physics: Conference Series 2096, no. 1 (November 1, 2021): 012018. http://dx.doi.org/10.1088/1742-6596/2096/1/012018.

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Abstract The paper presents an estimation of probability distributions of geoacoustic signal characteristics. The studied signals have a pulsed nature. The ones have been recording at the geodynamic test site of the IKIR FEB RAS (Kamchatka Peninsula) for more than 20 years. To estimate the distribution of characteristics, such time intervals were determined in which histograms of the distribution did not change. The following characteristics were chosen for the estimation: maximum amplitude, the position of pulse envelope maximum, duration, filling frequency, and pulse-to-pulse interval. The obtained estimates made it possible to develop an empirical model of the geoacoustic emission signal. The model can help to test new and existing algorithms for the processing and analysis of geoacoustic signals. The paper also shows that the formalization of the selected characteristics makes it possible to search for anomalies, including those associated with seismic events, by the characteristic variations.

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11

Kolpin, V. "How characteristic are characteristic functions?" International Journal of Game Theory 19, no. 3 (September 1990): 287–99. http://dx.doi.org/10.1007/bf01755479.

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12

Journal, Baghdad Science. "Some Probability Characteristics Functions of the Solution of a Stochastic Non-Linear Fredholm Integral Equation of the Second Kind." Baghdad Science Journal 8, no. 2 (June 5, 2011): 394–99. http://dx.doi.org/10.21123/bsj.8.2.394-399.

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In this research, some probability characteristics functions (probability density, characteristic, correlation and spectral density) are derived depending upon the smallest variance of the exact solution of supposing stochastic non-linear Fredholm integral equation of the second kind found by Adomian decomposition method (A.D.M)

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13

Pepe, Margaret Sullivan. "Receiver Operating Characteristic Methodology." Journal of the American Statistical Association 95, no. 449 (March 2000): 308–11. http://dx.doi.org/10.1080/01621459.2000.10473930.

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14

Kim, M. O., Hoyun Lee, Chil-Min Kim, Hyun-Soo Pang, Eok-Kyun Lee, and O. J. Kwon. "New Characteristic Relations in Type-II and III Intermittency." International Journal of Bifurcation and Chaos 07, no. 04 (April 1997): 831–36. http://dx.doi.org/10.1142/s0218127497000613.

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We obtained new characteristic relations in Type-II and III intermittencies according to the reinjection probability distribution. When the reinjection probability distribution is fixed at the lower bound of reinjection, the critical exponents are -1, as is well known. However when the reinjection probability distribution is uniform, the critical exponent is -1/2, and when it is of form [Formula: see text], -3/4. On the other hand, if the square root of Δ, which represents the lower bound of reinjection, is much smaller than the control parameter ∊, i.e. ∊ ≫ Δ1/2, critical exponent is always -1, independent of the reinjection probability distribution. Those critical exponents are confirmed by numerical simulation study.

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15

Zhang, Kui, Hong Dong Zhao, Tong Xi Shen, and Jie Huang. "Research of Probability Distribution of Semiconductor Test Parameter." Advanced Materials Research 1049-1050 (October 2014): 754–61. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.754.

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The probability distribution of electrical characteristic parameters of semiconductor device is an important reference which is used to analyze the reliability and quality consistency of devices. These distributions are considered as normal distribution at home and abroad. This paper utilized mature GaAs MESFET low noise amplifier as analytic sample which is volume production and wide application, and used high-precision Agilent B1505A device analyzer to test main electrical characteristics of 408 samples. After the distribution generation of test results, the Skewness-Kurtosis method was used to analyze probability distributions of the results. At last, the conclusion of distribution of measuring parameter is non-normal distribution was educed.

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16

Цзан, Ц., and Z. Zhang. "Bounds for characteristic functions and Laplace transforms of probability distributions." Teoriya Veroyatnostei i ee Primeneniya 56, no. 2 (2011): 407–14. http://dx.doi.org/10.4213/tvp4385.

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17

Meintanis, Simos G., Jan Swanepoel, and James Allison. "The probability weighted characteristic function and goodness-of-fit testing." Journal of Statistical Planning and Inference 146 (March 2014): 122–32. http://dx.doi.org/10.1016/j.jspi.2013.09.011.

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18

Schladitz, K., and H. J. Engelbert. "On Probability Density Functions Which are Their Own Characteristic Functions." Theory of Probability & Its Applications 40, no. 3 (January 1996): 577–81. http://dx.doi.org/10.1137/1140065.

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19

Zhang, Z. "Bounds for Characteristic Functions and Laplace Transforms of Probability Distributions." Theory of Probability & Its Applications 56, no. 2 (January 2012): 350–58. http://dx.doi.org/10.1137/s0040585x97985479.

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20

Hughett, Paul. "Error Bounds for Numerical Inversion of a Probability Characteristic Function." SIAM Journal on Numerical Analysis 35, no. 4 (August 1998): 1368–92. http://dx.doi.org/10.1137/s003614299631085x.

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21

Bohumir, Strnadel, Ivan Nedbal, Claude Prioul, and Masaki Shiratori. "Probability of brittle fracture instability and characteristic distance in steels." Proceedings of the 1992 Annual Meeting of JSME/MMD 2000 (2000): 193–94. http://dx.doi.org/10.1299/jsmezairiki.2000.0_193.

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22

Fakhry, Mohammed E. "Some Characteristic Properties of a Certain Family of Probability Distributions." Statistics 28, no. 2 (January 1996): 179–85. http://dx.doi.org/10.1080/02331889708802558.

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23

Kwapień, S., and V. Tarieladze. "Mackey Continuity of Characteristic Functionals." gmj 9, no. 1 (March 2002): 83–112. http://dx.doi.org/10.1515/gmj.2002.83.

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Abstract Problems of the Mackey-continuity of characteristic functionals and the localization of linear kernels of Radon probability measures in locally convex spaces are investigated. First the class of spaces is described, for which the continuity takes place. Then it is shown that in a non-complete sigmacompact inner product space, as well as in a non-complete sigma-compact metizable nuclear space, there may exist a Radon probability measure having a non-continuous characteristic functional in the Mackey topology and a linear kernel not contained in the initial space. Similar problems for moment forms and higher order kernels are also touched upon. Finally, a new proof of the result due to Chr. Borell is given, which asserts that any Gaussian Radon measure on an arbitrary Hausdorff locally convex space has the Mackey-continuous characteristic functional.

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24

Andronov, Alexander, and Maxim Fioshin. "Applications of resampling approach to statistical problems of logical systems." Acta et Commentationes Universitatis Tartuensis de Mathematica 8 (December 31, 2004): 63–71. http://dx.doi.org/10.12697/acutm.2004.08.02.

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The resampling approach to the problem of confidence interval construction is considered. An efficiency of this approach is investigated for logical system characteristics. Proposed method allows to calculate the probability that obtained interval coverstrue value of characteristic. Empirical results show that true covering probability is close to appointed value.

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25

Holgate, P. "The lognormal characteristic function." Communications in Statistics - Theory and Methods 18, no. 12 (January 1989): 4539–48. http://dx.doi.org/10.1080/03610928908830173.

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26

Cheng, Qiang, Can Wu, Peihua Gu, Wenfen Chang, and Dongsheng Xuan. "An Analysis Methodology for Stochastic Characteristic of Volumetric Error in Multiaxis CNC Machine Tool." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/863283.

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Traditional approaches about error modeling and analysis of machine tool few consider the probability characteristics of the geometric error and volumetric error systematically. However, the individual geometric error measured at different points is variational and stochastic, and therefore the resultant volumetric error is aslo stochastic and uncertain. In order to address the stochastic characteristic of the volumetric error for multiaxis machine tool, a new probability analysis mathematical model of volumetric error is proposed in this paper. According to multibody system theory, a mean value analysis model for volumetric error is established with consideration of geometric errors. The probability characteristics of geometric errors are obtained by statistical analysis to the measured sample data. Based on probability statistics and stochastic process theory, the variance analysis model of volumetric error is established in matrix, which can avoid the complex mathematics operations during the direct differential. A four-axis horizontal machining center is selected as an illustration example. The analysis results can reveal the stochastic characteristic of volumetric error and are also helpful to make full use of the best workspace to reduce the random uncertainty of the volumetric error and improve the machining accuracy.

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27

Su, Shu-Ching, Stephan A. Sedory, and Sarjinder Singh. "Adjusted Kuk's model using two non sensitive characteristics unrelated to the sensitive characteristic." Communications in Statistics - Theory and Methods 46, no. 4 (March 22, 2016): 2055–75. http://dx.doi.org/10.1080/03610926.2015.1040503.

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28

Langer, Adrian. "Semistable sheaves in positive characteristic." Annals of Mathematics 159, no. 1 (January 1, 2004): 251–76. http://dx.doi.org/10.4007/annals.2004.159.251.

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29

Berman, Simeon M., and Eugene Lukacs. "Developments in Characteristic Function Theory." Journal of the American Statistical Association 80, no. 392 (December 1985): 1070. http://dx.doi.org/10.2307/2288586.

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30

Welsh, A. H. "Implementing empirical characteristic function procedures." Statistics & Probability Letters 4, no. 2 (March 1986): 65–67. http://dx.doi.org/10.1016/0167-7152(86)90019-2.

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31

Gao, Lei Lei, and Xin Tao Xia. "Poor Information Analysis of Rolling Bearing Friction Torque Characteristic Parameter Based on Phase Space." Advanced Materials Research 382 (November 2011): 167–71. http://dx.doi.org/10.4028/www.scientific.net/amr.382.167.

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The friction torque of rolling bearings belongs to an information poor system with unknown probability distributions and trends. This counteracts dynamical assessment for the characteristics of the rolling bearing friction torque as a time series. For this reason, the chaos theory is employed to recover the original dynamic characteristics of a friction torque time series by means of the phase space reconstruction theory. The dynamical Bayesian probability density function of the characteristic parameters of the friction torque is constructed by the information poor theory based on the phase space. The method for point estimation, interval estimation, and trend estimation of the characteristic parameters is proposed in this paper. The investigation shows that the error between the calculated result and the experimental result is very small.

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32

Klein, Claude A. "Characteristic strength, Weibull modulus, and failure probability of fused silica glass." Optical Engineering 48, no. 11 (November 1, 2009): 113401. http://dx.doi.org/10.1117/1.3265716.

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33

Biscay, Rolando, and Roberto Pascual. "Distance between probability measures based on the relative operating characteristic curves." Statistics 24, no. 4 (January 1993): 371–76. http://dx.doi.org/10.1080/02331888308802424.

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34

Chen, Xiaoyue, Jianzhong Zhou, Han Xiao, Ercheng Wang, Jian Xiao, and Huifeng Zhang. "Fault diagnosis based on comprehensive geometric characteristic and probability neural network." Applied Mathematics and Computation 230 (March 2014): 542–54. http://dx.doi.org/10.1016/j.amc.2013.12.122.

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35

Dorodnov, A. A. "Approximate computation of characteristic functionals of some classes of probability measures." Journal of Soviet Mathematics 39, no. 5 (December 1987): 3003–9. http://dx.doi.org/10.1007/bf01093432.

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36

Karlová, A., and L. B. Klebanov. "Estimation of the Tail of Probability Distribution Through its Characteristic Function." Journal of Mathematical Sciences 229, no. 6 (February 21, 2018): 714–18. http://dx.doi.org/10.1007/s10958-018-3710-7.

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37

Kichaeva, Oxana. "Probability of brick structures destruction." ACADEMIC JOURNAL Series: Industrial Machine Building, Civil Engineering 1, no. 52 (July 5, 2019): 110–14. http://dx.doi.org/10.26906/znp.2019.52.1683.

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The results of calculations of construction brick destruction probability determination at central and off-center compressionare given; the determination of the brick structures destruction probability, caused by the exhaustion of the masonry strengthon local compression (crushing); determination of the brick structures destruction probability associated with the exhaustionof the masonry strength on the displacement (cut); determination of the brick structures destruction probability associatedwith the exhaustion of the masonry strength on the fold, the stretch; determination of the brick structures destruction probabilityon the crack opening. The value of the security characteristic for each case has been determined and the comparisonwith the normative values has been made.

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38

Schladitz, K., and A. J. Baddeley. "A Third Order Point Process Characteristic." Scandinavian Journal of Statistics 27, no. 4 (December 2000): 657–71. http://dx.doi.org/10.1111/1467-9469.00214.

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39

Gamkrelidze, N. G. "An Inequality for Multidimensional Characteristic Function." Theory of Probability & Its Applications 36, no. 3 (January 1992): 594–96. http://dx.doi.org/10.1137/1136071.

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40

Nadarajah, Saralees, and Tibor K. Pogány. "Characteristic function of the SGT distribution." Statistics 46, no. 4 (February 2, 2011): 437–39. http://dx.doi.org/10.1080/02331888.2010.538475.

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41

Pallini, Andrea. "On characteristic function-based bootstrap tests." Journal of the Italian Statistical Society 1, no. 1 (February 1992): 77–86. http://dx.doi.org/10.1007/bf02589051.

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42

Pallini, Andrea. "On characteristic function-based bootstrap tests." Journal of the Italian Statistical Society 1, no. 3 (December 1992): 431. http://dx.doi.org/10.1007/bf02589091.

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43

Melia, Hamish A., Christopher T. Chantler, Lucas F. Smale, and Alexis J. Illig. "The characteristic radiation of copper Kα1,2,3,4." Acta Crystallographica Section A Foundations and Advances 75, no. 3 (April 10, 2019): 527–40. http://dx.doi.org/10.1107/s205327331900130x.

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A characterization of the Cu Kα1,2 spectrum is presented, including the 2p satellite line, Kα3,4, the details of which are robust enough to be transferable to other experiments. This is a step in the renewed attempts to resolve inconsistencies in characteristic X-ray spectra between theory, experiment and alternative experimental geometries. The spectrum was measured using a rotating anode, monolithic Si channel-cut double-crystal monochromator and backgammon detector. Three alternative approaches fitted five Voigt profiles to the data: a residual analysis approach; a peak-by-peak fit; and a simultaneous constrained method. The robustness of the fit is displayed across three spectra obtained with different instrumental broadening. Spectra were not well fitted by transfer of any of three prior characterizations from the literature. Integrated intensities, line widths and centroids are compared with previous empirical fits. The novel experimental setup provides insight into the portability of spectral characterizations of X-ray spectra. From the parameterization, an estimated 3d shake probability of 18% and a 2p shake probability of 0.5% are reported.

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44

Lund, Emily. "Comparing Word Characteristic Effects on Vocabulary of Children with Cochlear Implants." Journal of Deaf Studies and Deaf Education 24, no. 4 (April 30, 2019): 424–34. http://dx.doi.org/10.1093/deafed/enz015.

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Abstract Many studies have evaluated overall vocabulary knowledge of children who use cochlear implants, but there has been minimal focus on how word form characteristics affect this knowledge. This study evaluates the effects of neighborhood density and phonotactic probability on the expressive vocabulary of 81 children between five and seven years old (n = 27 cochlear implant users, n = 27 children matched for chronological age, and n = 27 children matched for vocabulary size). Children were asked to name pictures associated with words that have common and rare phonotactic probability and high and sparse neighborhood density. Results indicate that children with cochlear implants, similar to both groups of children with typical hearing, tend to know words with common probability/high density or with rare probability/ sparse density. Patterns of word knowledge for children with cochlear implants mirrored younger children matched for vocabulary size rather than age-matched children with typical hearing.

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45

Datta, Gauri Sankar, and Malay Ghosh. "Characteristic Functions Without Contour Integration." American Statistician 61, no. 1 (February 2007): 67–70. http://dx.doi.org/10.1198/000313007x170422.

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46

Gneiting, Tilmann. "Onα-Symmetric Multivariate Characteristic Functions." Journal of Multivariate Analysis 64, no. 2 (February 1998): 131–47. http://dx.doi.org/10.1006/jmva.1997.1713.

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47

M Mustafa, Mustafa. "Nonlocality and the D-state Probability of the Deuteron." Australian Journal of Physics 45, no. 5 (1992): 643. http://dx.doi.org/10.1071/ph920643.

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48

Wijayanto, Dwi Agus, Rusli Hidayat, and Moh Hasan. "Application of Difference Equations Model in Determining Genotype Probability Offspring with Two Different Characteristic." Jurnal ILMU DASAR 14, no. 2 (December 4, 2013): 79. http://dx.doi.org/10.19184/jid.v14i2.90.

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Population genetics is a branch of biology which studies about the gene composition from population and the change of the gene composition is effect from some factors. One of them is lethal gene factor. The change of gene composition will influence the genotype probabilities in the population. In this paper discussed about determining the genotype for the probability of the n-th offspring genotypes in dihybrid mating by observing linkage between the two loci. The mating occurred randomly and without concern ethics in mating. This research was done by making mathematics model to determine allele pair, using difference equation, then from this model will be determined genotypes probability. The result show that the mating happened normally had the same genotype probability of each generation, meanwhile in abnormal mating, the genotype probability whose had lethal gene would decrease and the genotype probability whose did not have lethal gene would increase in each generation.Keywords : Difference equation, dihybrid mating, lethal gene, population genetics, probability

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49

Schnurr, Alexander. "The fourth characteristic of a semimartingale." Bernoulli 26, no. 1 (February 2020): 642–63. http://dx.doi.org/10.3150/19-bej1145.

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50

Ling, Jeeng Min, and Kunkerati Lublertlop. "The Estimation of Wind Speed and Wind Power Characteristics in Taiwan." Applied Mechanics and Materials 535 (February 2014): 145–48. http://dx.doi.org/10.4028/www.scientific.net/amm.535.145.

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In this paper, the Weibull, Gamma, Lognormal, Rayleigh probability density functions (PDF) were used to statistically analyze the characteristics of wind speed and evaluate the energy based on hourly records from years of 2004 to 2009 at 24 locations in Taiwan. Weibull model shows the best goodness probability density function for estimating behavior of wind characteristic within six years at 7 sites of weather station better than using the Gamma and Rayleigh model. The annual mean wind power density is estimated and compared by different index. The feasibility of probability distributions at different locations were investigated.

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