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Books on the topic 'Time Estimation Method'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Colombo, A. G. BANPES: A conversational computer programme for point and interval estimation of time-dependent failure rateby a Bayesian nonparametric method. Commission of the European Communities, 1986.

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2

Bee Dagum, Estela, and Silvia Bianconcini. Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31822-6.

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3

A, Whitmore Stephen, and Hugh L. Dryden Flight Research Center., eds. Real-time method for estimating viscous forebody drag coefficients. National Aeronautics and Space Administration, Dryden Flight Research Center, 2000.

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4

A, Whitmore Stephen, and Hugh L. Dryden Flight Research Center., eds. Real-time method for estimating viscous forebody drag coefficients. National Aeronautics and Space Administration, Dryden Flight Research Center, 2000.

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5

A, Whitmore Stephen, and Hugh L. Dryden Flight Research Center., eds. Real-time method for estimating viscous forebody drag coefficients. National Aeronautics and Space Administration, Dryden Flight Research Center, 2000.

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6

Mekaiel, Mohammed M. Bootstrap methods and parameter estimation in time series threshold modelling. University of Salford, 1995.

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7

Gibson, J. S. Computational methods for optimal linear-quadratic compensators for infinite dimensional discrete-time systems. ICASE, 1986.

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8

Ray, George, Bush Brian, National Renewable Energy Laboratory (U.S.), and Colorado Renewable Energy Conference (2009), eds. Estimating solar PV output using modern space/time geostatistics. National Renewable Energy Laboratory, 2009.

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9

Xiaolei, Zhu, and Research Institute for Advanced Computer Science (U.S.), eds. Stability and error estimation for component adaptive grid methods. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1994.

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10

Mella-Barral, Pierre. New methods for estimating nonlinear continuous time interest rate processes. Department of Applied Economics, University of Cambridge, 1994.

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11

Bell, Philip A. Trend estimation for small areas: From a continuing survey with controlled sample overlap. Australian Bureau of Statistics, 1998.

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12

Mélard, Guy. Méthodes de prévision à court terme. Editions de l'Université de Bruxelles, 1990.

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13

Associates, Dowling, Travel Model Improvement Program (U.S.), and Technology Sharing Program (U.S.), eds. Travel model speed estimation and post processing methods for air quality analysis: Final report. U.S. Dept. of Transportation, 1997.

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14

Bell, Philip A. Using state space models and composite estimation to measure the effects of telephone interviewing on labour force estimates. Australian Bureau of Statistics, 1998.

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15

Lin, Kenneth Shang-Kai. Estimating asymmetric information equilibrium labor market models from aggregate time series data. Institute of Economics, Academia Sinica, 1987.

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16

Bell, Philip A. The impact of sample rotation patterns and composite estimation on survey outcomes. Australian Bureau of Statistics, 1999.

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17

Smith, Steven G. Statistical evaluation of travel time estimation based on data from freeze-branded chinook salmon on the Snake River, 1982-1990. Bonneville Power Administration, 1993.

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18

Branson, Nicola. Re-weighting the OHS and LFS national household survey data to create a consistent series over time: A cross entropy estimation approach. Southern Africa Labour and Development Research Unit, University of Cape Town, 2009.

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19

Kihangi, Kyamwami. Mémoire du territoire de Walikale: Le testament de nos ancêtres. Blessing Publishers, 2018.

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20

J, Quadakkers W., Schütze Michael, European Federation of Corrosion, and Institute of Materials (London, England), eds. Cyclic oxidation of high temperature materials: Mechanisms, testing methods, characterisation and life time estimation ; proceedings of an EFC Workshop, Frankfurt/Main, 1999. Published for the European Federation of Corrosion by IOM Communications, 1999.

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21

Quadakkers, W. J. Cyclic oxidation of high temperature materials: Mechanisms, testing methods, characterisation and life time estimation : proceedings of an EFC Workshop, Frankfurt/Main, 1999. IOM Communications, 1999.

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22

Babeshko, Lyudmila, and Irina Orlova. Econometrics and econometric modeling in Excel and R. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.

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The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluati

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23

Babeshko, Lyudmila, Mihail Bich, and Irina Orlova. Econometrics and econometric modeling. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1141216.

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The textbook covers a wide range of issues related to econometric modeling. Regression models are the core of econometric modeling, so the issues of their evaluation, testing of assumptions, adjustment and verification are given a significant place. Various aspects of multiple regression models are included: multicollinearity, dummy variables, and lag structure of variables. Methods of linearization and estimation of nonlinear models are considered. An apparatus for evaluating systems of simultaneous and apparently unrelated equations is presented. Attention is paid to time series models. Deta

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24

G, Cleveland Theodore, Roussel Meghan C, Geological Survey (U.S.), Harris County Flood Control District, and Texas. Department of Transportation, eds. A method for estimating peak and time of peak streamflow from excess rainfall for 10- to 640- acre watersheds in the Houston, Texas, Metropolitan Area. U.S. Dept. of the Interior, U.S. Geological Survey, 2011.

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25

Hall, Alastair R. Generalized Method of Moments. Oxford University Press, Incorporated, 2004.

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26

Automatic Trend Estimation Springerbriefs in Physics. Springer, 2012.

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27

Hall, Alastair R. Generalized Method of Moments: Advanced Texts in Econometrics. Oxford University Press, 2005.

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28

Drukker, David M. Missing Data Methods: Time-Series Methods and Applications. Emerald Publishing Limited, 2011.

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29

Drukker, David M., Carter Hill, and Tom Fomby. Missing Data Methods: Time-Series Methods and Applications. Emerald Publishing Limited, 2011.

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30

Epstein, Charles L., and Rafe Mazzeo. Holder Estimates for Higher Dimensional Corner Models. Princeton University Press, 2017. http://dx.doi.org/10.23943/princeton/9780691157122.003.0007.

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This chapter establishes Hölder space estimates for higher dimensional corner model problems. It first explains the homogeneous Cauchy problem before estimating the solution of the inhomogeneous problem in a n-dimensional corner. It then reduces the proof of an estimate in higher dimensions to the estimation of a product of 1-dimensional integrals. Using the “1-variable-at-a-time” method, the chapter proves the higher dimensional estimates in several stages by considering the “pure corner” case where m = 0, and then turns to the Euclidean case, where n = 0. It also discusses the resolvent oper

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31

Cheng, Russell. Change-Point Models. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198505044.003.0011.

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This chapter investigates change-point (hazard rate) probability models for the random survival time in some population of interest. A parametric probability distribution is assumed with parameters to be estimated from a sample of observed survival times. If a change-point parameter, denoted by τ‎, is included to represent the time at which there is a discrete change in hazard rate, then the model is non-standard. The profile log-likelihood, with τ‎ as profiling parameter, has a discontinuous jump at every τ‎ equal to a sampled value, becoming unbounded as τ‎ tends to the largest observation.

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32

Dagum, Estela Bee, and Silvia Bianconcini. Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation. Springer International Publishing AG, 2016.

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33

Dagum, Estela Bee, and Silvia Bianconcini. Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation. Springer, 2018.

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34

Dagum, Estela Bee, and Silvia Bianconcini. Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation. Springer London, Limited, 2016.

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35

Straumann, Daniel. Estimation in Conditionally Heteroscedastic Time Series Models. Springer London, Limited, 2006.

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36

Speeckaert, Marijn, and Jopis Delanghe. Assessment of renal function. Edited by Christopher G. Winearls. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199592548.003.0007.

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Glomerular filtration rate (GFR) can be measured as the clearance of exogenous or endogenous filtration markers. Practical formulas permit estimation of creatinine clearance or GFR without timed urine collections in many stable patients with CKD. Standardization of serum creatinine is important for all of these estimation methods and implementing traceability of the assays to the new global SRM 967 standard has led to changes in clinical decision-making criteria. Calibration to an IDMS reference produces a lowering of serum creatinine values by 10–30% for most methods. Serum creatinine concent

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37

Robust time and frequency domain estimation methods in adaptive control. Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, 1987.

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38

Bond, W. Soil Physical Methods for Estimating Recharge - Part 3. CSIRO Publishing, 1998. http://dx.doi.org/10.1071/9780643105355.

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Measurements in and just below the plant root zone, using principles of soil physics, can be used to estimate recharge. This booklet describes the Zero Flux Plane Method, Methods Based on Darchy's law, and Lysimetry for making such estimates. The work presents the basic concepts of soil water physics that will be referred to in this and other booklets in the series. Another method, the Soil Water Flux Meter, is discussed briefly, but as this is not sufficiently well developed for routine use readers are referred elsewhere for full details. All these methods require that consideration be given

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39

A real-time method for estimating viscous forebody drag coefficients. National Aeronautics and Space Administration, Dryden Flight Research Center, 2000.

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40

Baker, Regina. Applied Time Series Analysis for the Social Sciences: Specification, Estimation, and Inference. Wiley & Sons, Incorporated, John, 2021.

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41

Baker, Regina. Applied Time Series Analysis for the Social Sciences: Specification, Estimation, and Inference. Wiley & Sons, Incorporated, John, 2021.

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42

Baker, Regina. Applied Time Series Analysis for the Social Sciences: Specification, Estimation, and Inference. Wiley & Sons, Incorporated, John, 2021.

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43

Baker, Regina. Applied Time Series Analysis for the Social Sciences: Specification, Estimation, and Inference. Wiley & Sons, Limited, John, 2021.

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44

Armstrong, D., and K. Narayan. Using Groundwater Responses to Infer Recharge - Part 5. CSIRO Publishing, 1998. http://dx.doi.org/10.1071/9780643105379.

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Analytical methods of assessing the response of groundwater levels to a range of factors, including elastic (barometric and tidal) influences in confined aquifers and recharge to unconfined aquifers due to infiltration of rain and other surface water, are presented. Responses in a confined aquifer to distant recharge events and the associated time lag is discussed. Also covered are responses to changes in storage volume resulting from direct recharge at the outcrop of an unconfined aquifer system both seasonally and on a single recharge event basis. Worked examples and case histories are used

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45

Stability and error estimation for component adaptive grid methods. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1994.

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46

Nonlinear time series: Semiparametric and nonparametric methods. Chapman & Hall/CRC, 2008.

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47

Gao, Jiti. Nonlinear Time Series: Semiparametric and Nonparametric Methods. Taylor & Francis Group, 2010.

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48

Gao, Jiti. Nonlinear Time Series: Semiparametric and Nonparametric Methods. Taylor & Francis Group, 2007.

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49

Gao, Jiti. Nonlinear Time Series: Semiparametric and Nonparametric Methods. Taylor & Francis Group, 2007.

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50

Parameter Estimation of Sinusodial Signals in Noise: Theory and Methods. Chapman & Hall/CRC, 2002.

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