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Books on the topic 'Ratio estimator'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Manno, Michael S. An evaluation of the odds ratio as an estimator of vaccine efficacy. National Library of Canada = Bibliothèque nationale du Canada, 1999.

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2

Seale, David Andrew. A statistical model of microarray images and an estimator of gene expression ratio. National Library of Canada, 2002.

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3

L, Musgrave Jeffrey, and United States. National Aeronautics and Space Administration., eds. A neural network-based estimator for the mixture ratio of the space shuttle main engine. National Aeronautics and Space Administration, 1992.

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4

J, Musgrave, and United States. National Aeronautics and Space Administration., eds. A neural network-based estimator for the mixture ratio of the space shuttle main engine. National Aeronautics and Space Administration, 1992.

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5

J, Musgrave, and United States. National Aeronautics and Space Administration., eds. A neural network-based estimator for the mixture ratio of the space shuttle main engine. National Aeronautics and Space Administration, 1992.

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6

Willem W. S. Van Hees. A comparison of two estimates of standard error for a ratio-of-means estimator for a mapped-plot sample design in Southeast Alaska. U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2002.

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7

1981-, Suzuki Taiji, and Kanamori Takafumi 1971-, eds. Density ratio estimation in machine learning. Cambridge University Press, 2012.

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8

Cecchetti, Stephen G. Structural estimates of the U.S. sacrifice ratio. Federal Reserve Bank of New York, 1999.

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9

Tomlinson, George. Confounder measurement error and exposure odds ratio estimation. National Library of Canada = Bibliothèque nationale du Canada, 1993.

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10

Baccour, Nouha, Anis Koubâa, Claro Noda, et al. Radio Link Quality Estimation in Low-Power Wireless Networks. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00774-8.

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11

Srivastava, M. S. Saddlepoint method for obtaining tail probability of Wilk's likelihood ratio test. University of Toronto, Dept. of Statistics, 1988.

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12

Godfrey, Matthew Howland. Sex ratios of sea turtle hatchlings: Direct and indirect estimates. National Library of Canada = Bibliothèque nationale du Canada, 1997.

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13

Bera, Anil K. A note on the arch effects in hedge ratio estimation: Stock index futures. Bureau of Economic and Business Research, 1986.

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14

Delaney, Brian. Dynamic hedging and time-varying optimal hedge ratio estimation with foreign currency futures. University College Dublin, 1995.

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15

Casey, Donal. Channel estimation techniques for mobile communications. University College Dublin, 1995.

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16

Oliveira-Martins, Joaquim. Mark-up ratios in manufacturing industries: Estimates for 14 OECD countries. OECD, 1996.

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17

Meyr, Heinrich. Digital communication receivers: Synchronization, channel estimation, and signal processing. Wiley, 1998.

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18

Singh, Ajit Kumar. Estimation of incremental capital output ratio in Uttar Pradesh: 2004-05 to 2009-10. Giri Institute of Development Studies, 2012.

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19

United States. National Telecommunications and Information Administration., ed. Estimation of system gain and bias using noisy observations with known noise power ratio. U.S. Dept. of Commerce, National Telecommunications and Information Administration, 2002.

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20

S, Panageas Katherine. Statistics in periodontal research: Interval estimation of the common odds ratio under cluster sampling. [Columbia University], 1998.

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21

Lin, Lao-Sheng. Real-time estimation of ionospheric delay using GPS measurements. School of Geomatic Engineering, University of New South Wales, 1998.

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22

Bera, Anil K. Estimation of time-varying hedge ratios for corn and soybeans: BGARCH and random coefficient approaches. Bureau of Economic and Business Research, University of Illinois at Urbana-Champaign, 1992.

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23

L, Fanselow J., and Jet Propulsion Laboratory (U.S.), eds. Observation model and parameter partials for the JPL VLBI parameter estimation software MASTERFIT, 1987. National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1988.

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24

Commerce, United States Congress House Committee on. Radio Broadcasting Preservation Act of 2000: Report (to accompany H.R. 3439) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 2000.

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25

Commerce, United States Congress Senate Committee on. Radio Broadcasting Preservation Act of 2000: Report (to accompany H.R. 3439) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 2000.

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26

Commerce, United States Congress House Committee on. Radio Broadcasting Preservation Act of 2000: Report (to accompany H.R. 3439) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 2000.

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27

Manning, Robert Michael. Real-time in situ signal-to-noise ratio estimation for the assessment of operational communications links. National Aeronautics and Space Administration, Glenn Research Center, 2002.

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28

Manning, Robert Michael. Real-time in situ signal-to-noise ratio estimation for the assessment of operational communications links. National Aeronautics and Space Administration, Glenn Research Center, 2002.

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29

Manning, Robert Michael. Real-time in situ signal-to-noise ratio estimation for the assessment of operational communications links. National Aeronautics and Space Administration, Glenn Research Center, 2002.

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30

Spray, Judith A. The effect of item parameter estimation error on decisions made using the sequential probability ratio test. American College Testing Program, 1988.

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31

Manning, Robert Michael. Real-time in situ signal-to-noise ratio estimation for the assessment of operational communications links. National Aeronautics and Space Administration, Glenn Research Center, 2002.

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32

Benjamin, Friedlander, Knovel (Firm), and ScienceDirect (Online service), eds. Classical and modern direction-of-arrival estimation. Academic Press/Elsevier, 2009.

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33

A, Schowengerdt Robert, and Research Institute for Advanced Computer Science (U.S.), eds. The effect of lossy image compression on image classification. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1995.

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34

Götz, Alexander. Coherent Time Difference of Arrival Estimation Techniques for Frequency Hopping GSM Mobile Radio Signals. Oldenbourg Wissenschaftsverlag Verlag, 2013. http://dx.doi.org/10.1524/9783486748628.

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35

J, Sovers O., and Jet Propulsion Laboratory (U.S.), eds. Observation model and parameter partials for the JPL VLBI parameter estimation software "MASTERFIT-V2.0". National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1985.

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36

Jolicoeur, Hélène. Estimation de la densité d'ours noirs dans différents types de végétation a l'aide de traceurs radioactifs période 1984-1994. Ministère des Ressources naturelles, de la Faune et des Parcs, 2004.

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37

United States. Congress. House. Committee on International Relations. Radio Free Asia Act of 1997: Report (to accompany H.R. 2232) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 1997.

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38

United States. Congress. House. Committee on Energy and Commerce. Emerging Telecommunications Technologies Act of 1990: Report (to accompany H.R. 2965) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 1990.

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39

United States. Congress. House. Committee on Merchant Marine and Fisheries. EPIRB's on Uninspected Vessels Requirements Act: Report (to accompany H.R. 4557) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 1988.

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40

United States. Congress. House. Committee on Merchant Marine and Fisheries. EPIRB's on Uninspected Vessels Requirements Act: Report (to accompany H.R. 4557) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 1988.

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41

United States. Congress. House. Committee on Energy and Commerce. Broadcast Decency Enforcement Act of 2005: Report (to accompany H.R. 310) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 2005.

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42

United States. Congress. House. Committee on Merchant Marine and Fisheries. EPIRB's on Uninspected Vessels Requirements Act: Report (to accompany H.R. 4557) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 1988.

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43

United States. Congress. House. Committee on Energy and Commerce. Emerging Telecommunications Technologies Act of 1993: Report (to accompany H.R. 707) (including cost estimate of the Congressional Budget Office). U.S. G.P.O., 1993.

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44

United States. Congress. House. Committee on the Judiciary, ed. Wireless Telecommunications Sourcing and Privacy Act: Report (to accompany H.R. 3489) (including cost estimate of the Congressional Budget Office). [U.S. G.P.O.], 2000.

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45

United States. National Aeronautics and Space Administration., ed. REAL-TIME IN SITU SIGNAL-TO-NOISE RATIO ESTIMATION FOR THE ASSESSMENT OF OPERATIONAL..., NASA/TM--2002-211703... NATIONAL AERONAUTICS AND SP. s.n., 2003.

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46

Takagi, Hirofumi. Program on the conditional maximum likelihood estimate of the common odds ratio and the AIC in the analysis of K 2x2 tables. Institute of Statistical Mathematics, 1991.

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47

Cheng, Russell. Standard Asymptotic Theory. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198505044.003.0003.

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Abstract:

This book relies on maximum likelihood (ML) estimation of parameters. Asymptotic theory assumes regularity conditions hold when the ML estimator is consistent. Typically an additional third derivative condition is assumed to ensure that the ML estimator is also asymptotically normally distributed. Standard asymptotic results that then hold are summarized in this chapter; for example, the asymptotic variance of the ML estimator is then given by the Fisher information formula, and the log-likelihood ratio, the Wald and the score statistics for testing the statistical significance of parameter es

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48

A neural network-based estimator for the mixture ratio of the space shuttle main engine. National Aeronautics and Space Administration, 1992.

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49

Walsh, Bruce, and Michael Lynch. Using Molecular Data to Detect Selection: Signatures from Multiple Historical Events. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0010.

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This chapter examines the search for a pattern of repetitive adaptive substitutions over evolutionary time. In contrast with the previous chapter, only a modest number of tests toward this aim have been proposed. The HKA and McDonald-Kreitman tests contrast the polymorphism to divergence ratio between different genomic classes (such as different genes or silent versus replacement sites within the same gene). These approaches can detect an excess of substitutions, which allows one to estimate the fraction of adaptive sites. This chapter reviews the empirical data on estimates of this fraction a

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50

Sugiyama, Masashi, Taiji Suzuki, and Takafumi Kanamori. Density Ratio Estimation in Machine Learning. Cambridge University Press, 2012.

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