Relevant bibliographies by topics / Continuous estimation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Continuous estimation'

Author: Grafiati
Published: 4 June 2025
Last updated: 23 June 2025

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Journal articles on the topic "Continuous estimation"

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Ashkenazi, Sarit, Yarden Gliksman, and Avishai Henik. "Understanding Estimations of Magnitudes: An fMRI Investigation." Brain Sciences 12, no. 1 (2022): 104. http://dx.doi.org/10.3390/brainsci12010104.

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The current study examined whether discrete numerical estimation is based on the same cognitive process as estimation of continuous magnitudes such as weight and time. While the verbal estimation of numerical quantities has a contingent unit of measurement (e.g., how many cookies fit in a cookie jar? _X_ cookies), estimation of time and weight does not (e.g., how much time does it take to fill a bath with water? _X_ minutes/hours/seconds). Therefore, estimation of the latter categories has another level of difficulty, requiring extensive involvement of cognitive control. During a functional magnetic resonance imaging (fMRI) scan, 18 students performed estimations with three estimation categories: number, time, and weight. Estimations elicited activity in multiple brain regions, mainly: (1) visual regions including bilateral lingual gyrus), (2) parietal regions including the left angular gyrus and right supramarginal gyrus, and (3) the frontal regions (cingulate gyrus and the inferior frontal cortex). Continuous magnitude estimations (mostly time) produced different frontal activity than discrete numerical estimations did, demonstrating different profiles of brain activations between discrete numerical estimations and estimations of continuous magnitudes. The activity level in the right middle and inferior frontal gyrus correlated with the tendency to give extreme responses, signifying the importance of the right prefrontal lobe in estimations.
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Obiri, Sandra A., Bernard T. Agyeman, Sarupa Debnath, Siyu Liu, and Jinfeng Liu. "Sensor Selection and State Estimation of Continuous mAb Production Processes." Mathematics 11, no. 18 (2023): 3860. http://dx.doi.org/10.3390/math11183860.

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The production of monoclonal antibodies (mAbs) plays a pivotal role in therapeutic treatments, and optimizing their production is crucial for minimizing costs and improving their accessibility to patients. One way of improving the production process is to improve model accuracy through the correct estimation of its states and parameters. The contributions of this paper lie in the provision of guidelines for sensor selection in the upstream production process of mAbs to enhance the accuracy of state estimation. Furthermore, this paper applies an effective variable selection technique for simultaneous state and parameter estimations for enhanced estimation results in the biomanufacturing processes of mAbs. An estimation framework of MHE is designed for three different case studies to demonstrate the efficiency of the proposed approach. The estimation performance is compared and assessed using the Root Mean Squared Error (RMSE) as an evaluation criterion.
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Zinde-Walsh, Victoria. "KERNEL ESTIMATION WHEN DENSITY MAY NOT EXIST." Econometric Theory 24, no. 3 (2008): 696–725. http://dx.doi.org/10.1017/s0266466608080298.

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Nonparametric kernel estimation of density and conditional mean is widely used, but many of the pointwise and global asymptotic results for the estimators are not available unless the density is continuous and appropriately smooth; in kernel estimation for discrete-continuous cases smoothness is required for the continuous variables. Nonsmooth density and mass points in distributions arise in various situations that are examined in empirical studies; some examples and explanations are discussed in the paper. Generally, any distribution function consists of absolutely continuous, discrete, and singular components, but only a few special cases of nonparametric estimation involving singularity have been examined in the literature, and asymptotic theory under the general setup has not been developed. In this paper the asymptotic process for the kernel estimator is examined by means of the generalized functions and generalized random processes approach; it provides a unified theory because density and its derivatives can be defined as generalized functions for any distribution, including cases with singular components. The limit process for the kernel estimator of density is fully characterized in terms of a generalized Gaussian process. Asymptotic results for the Nadaraya–Watson conditional mean estimator are also provided.
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Xu, Ke-Li. "REWEIGHTED FUNCTIONAL ESTIMATION OF DIFFUSION MODELS." Econometric Theory 26, no. 2 (2009): 541–63. http://dx.doi.org/10.1017/s0266466609100087.

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The local linear method is popular in estimating nonparametric continuous-time diffusion models, but it may produce negative results for the diffusion (or volatility) functions and thus lead to insensible inference. We demonstrate this using U.S. interest rate data. We propose a new functional estimation method of the diffusion coefficient based on reweighting the conventional Nadaraya–Watson estimator. It preserves the appealing bias properties of the local linear estimator and is guaranteed to be nonnegative in finite samples. A limit theory is developed under mild requirements (recurrence) of the data generating mechanism without assuming stationarity or ergodicity.
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Qin, Yongming, Makoto Kumon, and Tomonari Furukawa. "Estimation of a Human-Maneuvered Target Incorporating Human Intention." Sensors 21, no. 16 (2021): 5316. http://dx.doi.org/10.3390/s21165316.

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This paper presents a new approach for estimating the motion state of a target that is maneuvered by an unknown human from observations. To improve the estimation accuracy, the proposed approach associates the recurring motion behaviors with human intentions, and models the association as an intention-pattern model. The human intentions relate to labels of continuous states; the motion patterns characterize the change of continuous states. In the preprocessing, an Interacting Multiple Model (IMM) estimation technique is used to infer the intentions and extract motions, which eventually construct the intention-pattern model. Once the intention-pattern model has been constructed, the proposed approach incorporate the intention-pattern model to estimation using any state estimator including Kalman filter. The proposed approach not only estimates the mean using the human intention more accurately but also updates the covariance using the human intention more precisely. The performance of the proposed approach was investigated through the estimation of a human-maneuvered multirotor. The result of the application has first indicated the effectiveness of the proposed approach for constructing the intention-pattern model. The ability of the proposed approach in state estimation over the conventional technique without intention incorporation has then been demonstrated.
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Chen, Ziyang, Yichen Zhang, Xiangyu Wang, Song Yu, and Hong Guo. "Improving Parameter Estimation of Entropic Uncertainty Relation in Continuous-Variable Quantum Key Distribution." Entropy 21, no. 7 (2019): 652. http://dx.doi.org/10.3390/e21070652.

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The entropic uncertainty relation (EUR) is of significant importance in the security proof of continuous-variable quantum key distribution under coherent attacks. The parameter estimation in the EUR method contains the estimation of the covariance matrix (CM), as well as the max-entropy. The discussions in previous works have not involved the effect of finite-size on estimating the CM, which will further affect the estimation of leakage information. In this work, we address this issue by adapting the parameter estimation technique to the EUR analysis method under composable security frameworks. We also use the double-data modulation method to improve the parameter estimation step, where all the states can be exploited for both parameter estimation and key generation; thus, the statistical fluctuation of estimating the max-entropy disappears. The result shows that the adapted method can effectively estimate parameters in EUR analysis. Moreover, the double-data modulation method can, to a large extent, save the key consumption, which further improves the performance in practical implementations of the EUR.
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Galli, Brian J. "Cost Estimation Methods in Quality Management and Continuous Improvement." International Journal of Service Science, Management, Engineering, and Technology 12, no. 1 (2021): 38–61. http://dx.doi.org/10.4018/ijssmet.2021010103.

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This paper investigated cost estimation methods and continuous improvement in terms of project management planning, as well as the factors that influenced these actions. Estimating the cost was one of the most imperative tasks to be done by the managers for a project. Key factors, such as cost, size, schedule, quality, people resources, maintenance costs, and complexity, were usually estimated in the beginning of project development. The techniques used for cost estimation included data composed from past projects that were combined with mathematical formulae to get the closest estimation. In regards to continuous improvement, the four-step quality model (PDCA cycle) was used as an ongoing effort to improve products or services. PDCA stands for plan, do, check, and act, which were the steps to successfully implement change. Notably, project management, when tasked with cost estimation and continuous improvement, was challenged to cope with evolving and situational alterations, which required a different set of skills.
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Zatsepa, S. N., A. A. Ivchenko, V. V. Solbakov, and V. V. Stanovoy. "Some engineering estimations of oil spill parameters in the marine environment." Arctic and Antarctic Research 64, no. 2 (2018): 208–11. http://dx.doi.org/10.30758/0555-2648-2018-64-2-208-211.

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Estimation of the oil spill size at continuous spills on the moving sea surface or on the drifting ice field is the actual practical problem. Engineering estimation means the reduction of the hydrodynamic equations system to the balance of only two main forces that cause movement and resistance of the oil flow. From the simplified problem statement some practical relations were obtained for estimating the size of spill, including continuous oil spill with surface water currents presence, for spill onto porous snow-ice cover and onto the drifting ice cover. The obtained estimations can be used in more complicated models of oil spill transformation in the marine environment, primarily in the Arctic zone, and give basis for development of adequate responses on oil spills. The comparison of the obtained estimates with the self-similar solutions of the corresponding equations of motion of the spreading substance shows a satisfactory fit.
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Overbeck, Ludger. "Estimation for Continuous Branching Processes." Scandinavian Journal of Statistics 25, no. 1 (1998): 111–26. http://dx.doi.org/10.1111/1467-9469.00092.

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Kotchoni, Rachidi. "The indirect continuous-GMM estimation." Computational Statistics & Data Analysis 76 (August 2014): 464–88. http://dx.doi.org/10.1016/j.csda.2013.09.023.

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Dissertations / Theses on the topic "Continuous estimation"

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Gonzalez, Olivares Daniel. "Estimation of cointegrated systems in continuous time." Thesis, University of Essex, 2017. http://repository.essex.ac.uk/21093/.

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In this thesis we derive exact discrete time representation models that correspond to cointegrated systems in continuous time. At the same time, for the parameters of those models, estimation procedures are outlined. The representations are applicable for data observed as both stock or flow variables and with the use of some simulated data, the performance of the estimation procedure is assessed. More importantly, with the aim of analysing the costs, if there are any, of ignoring aggregation in the specification, the results of our estimation procedure are also compared with the ones we would have obtained by applying instead Johansen’s estimation methodology. In the first part (Chapter 2), we detail the analysis for a first- order stochastic differential equation system, as a result, baseline finding are outlined. In the second part (Chapter 3) the analysis is generalized and not only includes higher order specifications in the system but also incorporates deterministic components on it. Finally, in the last part (Chapter 4) of this thesis, three applications of that estimation procedure are presented. In the results, when the system is entirely comprised by stock variables and the specification follows a first order system, both Johansen’s methodology and ours perform very well, with virtually identical estimates and, for the simulated data, improvements as the sample size increases. However, when the variables of interest are flows or the specification follows a higher order system, given that our exact discrete time representation includes moving average components in the error term, Johansen’s estimates show a persistent bias in estimation, consequently, they reflected the cost of ignoring aggregation in the specification.
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Sinisalo, Jukka. "Estimation of greenhouse impacts of continuous regional emissions /." Espoo : Technical Research Centre of Finland, 1998. http://www.vtt.fi/inf/pdf/publications/1998/P338.pdf.

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Rahgozar, Mandana Seyed. "Estimation of evapotranspiration using continuous soil moisture measurement." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001812.

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Mujica, Fernando Alberto. "Spatio-temporal continuous wavelet transform for motion estimation." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/15001.

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Zhou, Aimin. "Estimation of distribution algorithms for continuous multiobjective optimization." Thesis, University of Essex, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.499770.

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Gillberg, Jonas. "Methods for frequency domain estimation of continuous-time models /." Linköping : univ, 2004. http://www.control.isy.liu.se.

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Sanyang, Momodou Lamin. "Large scale estimation of distribution algorithms for continuous optimisation." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7847/.

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Modern real world optimisation problems are increasingly becoming large scale. However, searching in high dimensional search spaces is notoriously difficult. Many methods break down as dimensionality increases and Estimation of Distribution Algorithm (EDA) is especially prone to the curse of dimensionality. In this thesis, we device new EDA variants that are capable of searching in large dimensional continuous domains. We in particular (i) investigated heavy tails search distributions, (ii) we clarify a controversy in the literature about the capabilities of Gaussian versus Cauchy search distributions, (iii) we constructed a new way of projecting a large dimensional search space to low dimensional subspaces in a way that gives us control of the size of covariance of the search distribution and we develop adaptation techniques to exploit this and (iv) we proposed a random embedding technique in EDA that takes advantage of low intrinsic dimensional structure of problems. All these developments avail us with new techniques to tackle high dimensional optimization problems.
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Woodson, David. "Precipitation Estimation Methods in Continuous, Distributed Urban Hydrologic Modeling." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/90373.

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Quantitative precipitation estimation (QPE) remains a key area of uncertainty in hydrological modeling, particularly in small, urban watersheds which respond rapidly to precipitation and can experience significant spatial variability in rainfall fields. Few studies have compared QPE methods in small, urban watersheds, and studies which have examined this topic only compared model results on an event basis using a small number of storms. This study sought to compare the efficacy of multiple QPE methods when simulating discharge in a small, urban watershed on a continuous basis using an operational hydrologic model and QPE forcings. The Research Distributed Hydrologic Model (RDHM) was used to model a basin in Roanoke, Virginia, USA forced with QPEs from four methods: mean field bias (MFB) correction of radar data, kriging of rain gauge data, uncorrected radar data, and a basin-uniform estimate from a single gauge inside the watershed. Based on comparisons between simulated and observed discharge at the basin outlet for a 6-month period in 2018, simulations forced with the uncorrected radar QPE had the highest accuracy, as measured by root mean square error (RMSE) and peak flow relative error, despite systematic underprediction of the mean areal precipitation (MAP). Simulations forced with MFB corrected radar data consistently and significantly overpredicted discharge but had the highest accuracy in predicting the timing of peak flows.<br>Master of Science<br>Estimating the amount of rain that fell during a precipitation event remains a key source of error when predicting how much stormwater runoff will be produced, particularly in small, urban watersheds which respond rapidly to precipitation and can experience significant spatial variability in rainfall distribution. Rainfall estimation in small, urban watersheds has received relatively little attention, and studies which have examined this topic have generally only examined a small number of discrete storm events. This study sought to compare the efficacy of multiple precipitation estimation methods when simulating discharge in a small, urban watershed on a continuous basis using an operational hydrologic model and precipitation inputs. The Research Distributed Hydrologic Model (RDHM), commonly used by the National Weather Service, was used to model a basin in Roanoke, Virginia, USA forced with rainfall estimates from four methods: mean field bias (MFB) correction of radar data, kriging of rain gauge data, uncorrected radar data, and a basin-uniform estimate from a single gauge inside the watershed. Based on comparisons between simulated and observed discharge at the basin outlet for a 6-month period in 2018, simulations forced with the uncorrected radar QPE had the highest accuracy, as measured by several performance statistics, despite systematic underprediction of actual precipitation. Simulations forced with MFB corrected radar data consistently and significantly overpredicted discharge but had the highest accuracy in predicting the timing of peak flows.
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VARINI, ELISA. "Sequential estimation methods in continuous time state place models." Doctoral thesis, Università Bocconi, 2006. http://hdl.handle.net/11565/4050376.

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Invernizzi, C. "QUANTUM ESTIMATION DISCRIMINATION IN CONTINUOUS VARIABLE AND FERMIONIC SYSTEMS." Doctoral thesis, Università degli Studi di Milano, 2011. http://hdl.handle.net/2434/158085.

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In this PhD thesis we address the problem of characterizing quantum states and parameters of systems that are of particular interest for quantum technologies. In the first part we consider continuous variable systems and in particular Gaussian states; we address the estimation of quantities characterizing single-mode Gaussian states as the displacement and squeezing parameter and we study the improvement in the parameter estimation by introducing a Kerr nonlinearity. Moreover, we address the discrimination of noisy channels by means of Gaussian states as probe states considering two problems: the detection of a lossy channel against the alternative hypothesis of an ideal lossless channel and the discrimination of two Gaussian noisy channels. In the last part of the thesis, we consider the one dimensional quantum Ising model in a transverse magnetic field. We exploit the recent results about the geometric approach to quantum phase transitions to derive the optimal estimator of the coupling constant of the model at zero and finite temperature in both cases of few spins and in the thermodynamic limit. We also analyze the effects of temperature and the scaling properties of the estimator of the coupling constant. Finally, we consider the discrimination problem for two ground states or two thermal states of the model.
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Books on the topic "Continuous estimation"

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Melino, Angelo. Estimation of continuous-time models in finance. Dept. of Economics and Institute for Policy Analysis, University of Toronto, 1991.

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Perraudin, William R. M. Continuous time international arbitrage pricing: Theory and estimation. University of Cambridge Department of Applied Economics, 1994.

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Sinisalo, Jukka. Estimation of greenhouse impacts of continuous regional emissions. VTT, Technical Research Centre of Finland, 1998.

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Chambers, Marcus J. Estimation of a continuous time dynamic demand system. University ofEssex, Dept. of Economics, 1989.

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Kulikov, Gennady Yu, and Maria V. Kulikova. State Estimation for Nonlinear Continuous–Discrete Stochastic Systems. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-61371-5.

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Chambers, Marcus J. The estimation of continuous parameter long-memory time series models. Essex University, Department of Economics, 1992.

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Hu, Chih-Chi. Sequential Quantile Estimation Using Continuous Outcomes with Applications in Dose Finding. [publisher not identified], 2014.

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K, Kar S., ed. Continuous time dynamical systems: State estimation and optimal control with orthogonal functions. CRC Press, 2013.

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Bederman, S. Samuel. Estimation methods in random coefficient regression for continuous and binary longitudinal data. National Library of Canada = Bibliothèque nationale du Canada, 1999.

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Bergstrom, A. R. Gaussian estimation of a continuous time model of demand for consumer durable goods. University of Essex, Dept. of Economics, 1988.

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Book chapters on the topic "Continuous estimation"

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Subrahmanyam, Allamaraju, and Ganti Prasada Rao. "Robust Parameter Estimation." In Identification of Continuous-Time Systems. CRC Press, 2019. http://dx.doi.org/10.1201/9780429352850-4.

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Hainaut, Donatien. "Particle Filtering and Estimation." In Continuous Time Processes for Finance. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06361-9_3.

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Wymer, Clifford R. "Continuous-time models in macroeconomics: specification and estimation." In Continuous-Time Econometrics. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1542-1_3.

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Hainaut, Donatien. "Switching Models: Properties and Estimation." In Continuous Time Processes for Finance. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06361-9_1.

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Poor, H. Vincent. "Signal Estimation in Continuous Time." In Springer Texts in Electrical Engineering. Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4757-2341-0_7.

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Poor, H. Vincent. "Signal Estimation in Continuous Time." In Springer Texts in Electrical Engineering. Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4757-3863-6_7.

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Bengoetxea, E., T. Miquélez, P. Larrañaga, and J. A. Lozano. "Experimental Results in Function Optimization with EDAs in Continuous Domain." In Estimation of Distribution Algorithms. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1539-5_8.

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Talbot-Pedersen, A., M. R. Neuman, G. M. Saidel, and E. Jacobsen. "Estimation of the Determinants of Transcutaneous Oxygen Tension Using a Dynamic Computer Model." In Continuous Transcutaneous Monitoring. Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1927-6_49.

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Hand, David, and Martin Crowder. "Continuous non-normal measures: Gaussian estimation." In Practical Longitudinal Data Analysis. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4899-3033-0_7.

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Shahraki, Shahram, and Mohammad Reza Akbarzadeh Tutunchy. "Continuous Gaussian Estimation of Distribution Algorithm." In Synergies of Soft Computing and Statistics for Intelligent Data Analysis. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33042-1_23.

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Conference papers on the topic "Continuous estimation"

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Liu, Hanlin, Lei Zhang, Zhengrong Chen, Shui Liu, Baiqiang Liang, and Yuehui Deng. "Continuous DOA estimation via tensorized LSTM." In Sixteenth International Conference on Signal Processing Systems (ICSPS 2024), edited by Robert Minasian and Li Chai. SPIE, 2025. https://doi.org/10.1117/12.3061641.

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Zhou, Rui, Naiming Qi, Shuanli Jia, et al. "Kalman-based continuous pose estimation network for spacecraft." In First Aerospace Frontiers Conference (AFC 2024), edited by Han Zhang. SPIE, 2024. http://dx.doi.org/10.1117/12.3032451.

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Bang, Sunwoo, Chaeyeong Lee, Junhyeong Ryu, Hyung Tae Lee, and Jeongyeup Paek. "Trend Shift in Pose Estimation: Toward Continuous Representation." In 2024 15th International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2024. https://doi.org/10.1109/ictc62082.2024.10827211.

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Ohno, Tetsushi, Hidehiko Sekiya, Ikumasa Yoshida, Ryotaro Wada, Atsushi Yasuda, and Keiko Tateno. "Fundamental Study on Continuous Estimation of Vertical Displacement during PC Bridge Construction." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.2102.

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&lt;p&gt;This study focuses on continuous vertical displacement estimation in PC bridges constructed using the balanced cantilever method. Traditional leveling surveys are labor-intensive and limited to specific moments, hindering efficiency. Using strain and rotation angle data from sensors installed on the bridge, continuous vertical displacement estimation is proposed. The estimation accuracy was validated by comparing results with leveling surveys. Results closely matched leveling survey data, demonstrating the method's accuracy. Sensors were placed on the bridge's lower deck to minimize temperature effects. Continuous monitoring captured deformation during construction, addressing challenges in traditional surveys.&lt;/p&gt;
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Reimann, Hans, Sarat Moka, and Georgy Sofronov. "Continuous Optimization for Offline Change Point Detection and Estimation." In 2024 Winter Simulation Conference (WSC). IEEE, 2024. https://doi.org/10.1109/wsc63780.2024.10838722.

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Matoušek, J., J. Duník, and M. Brandner. "Efficient Spectral Differentiation in Grid-Based Continuous State Estimation." In 2024 27th International Conference on Information Fusion (FUSION). IEEE, 2024. http://dx.doi.org/10.23919/fusion59988.2024.10706533.

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Nascimento, Vitor H., and Ali H. Sayed. "Continuous-time distributed estimation." In 2011 45th Asilomar Conference on Signals, Systems and Computers. IEEE, 2011. http://dx.doi.org/10.1109/acssc.2011.6190323.

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Felemban, Haitham B., Jiaxing Che, Chengyu Cao, Naira Hovakimyan, and Irene M. Gregory. "Estimation of Airspeed Using Continuous Polynomial Adaptive Estimator." In AIAA Guidance, Navigation, and Control Conference. American Institute of Aeronautics and Astronautics, 2014. http://dx.doi.org/10.2514/6.2014-0267.

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Currie, Stephanie Marie, Dilhan Ilk, and Tom Blasingame. "Continuous Estimation of Ultimate Recovery." In SPE Unconventional Gas Conference. Society of Petroleum Engineers, 2010. http://dx.doi.org/10.2118/132352-ms.

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Currie, Stephanie, Dilhan Ilk, and Tom Blasingame. "Continuous Estimation of Ultimate Recovery." In SPE Unconventional Gas Conference. Society of Petroleum Engineers, 2010. http://dx.doi.org/10.2523/132352-ms.

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Reports on the topic "Continuous estimation"

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Arcidiacono, Peter, Attila Gyetvai, Arnaud Maurel, and Ekaterina Jardim. Identification and Estimation of Continuous-Time Job Search Models with Preference Shocks. National Bureau of Economic Research, 2022. http://dx.doi.org/10.3386/w30655.

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Dormann, Christian. Introduction to Continuous Time Structural Equation Modeling (CTSEM). Instats Inc., 2023. http://dx.doi.org/10.61700/kwigtxevhohxk469.

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This seminar introduces the use of Continuous Time Structural Equation Modeling (CTSEM) to study phenomena over time in the social and health sciences. Day 1 topics include the required conceptual background, mathematical foundations, as well as examples to illustrate the concepts. On Day 2, the R package [b]ctsem [/b]is introduced, with hands-on coverage of topics including data preparation, model setup, parameter estimation, and interpretation of results. Day 3 topics include random intercept modelling (aka., within-person analysis), moderator analysis, and an outlook to Continuous Time Meta-Analysis (CoTiMA) using results from multiple studies. An official Instats certificate of completion is provided at the conclusion of the seminar. The seminar offers 2 ECTS Equivalent points for European PhD students.
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Casinovi, Giorgio. Development of Cad Tools for Power Estimation in Continuous-Time and Switched-Capacitor Analog Circuits. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada373430.

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Casinovi, Giorgio. Development of CAD Tools for Power Estimation in Continuous-Time and Switched-Capacitor Analog Circuits. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada375770.

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Arcidiacono, Peter, Patrick Bayer, Jason Blevins, and Paul Ellickson. Estimation of Dynamic Discrete Choice Models in Continuous Time with an Application to Retail Competition. National Bureau of Economic Research, 2012. http://dx.doi.org/10.3386/w18449.

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Dormann, Christian. Introduction to Continuous Time Structural Equation Modeling (CTSEM) + 1 Free Seminar. Instats Inc., 2022. http://dx.doi.org/10.61700/am2g78fjl1gx5469.

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Abstract:
This seminar introduces the use of Continuous Time Structural Equation Modeling (CTSEM) to study phenomena over time in the social and health sciences. Day 1 topics include the required conceptual background, mathematical foundations, as well as examples to illustrate the concepts. On Day 2, the R package [b]ctsem [/b]is introduced, with hands-on coverage of topics including data preparation, model setup, parameter estimation, and interpretation of results. Day 3 topics include random intercept modelling (aka., within-person analysis), moderator analysis, and an outlook to Continuous Time Meta-Analysis (CoTiMA) using results from multiple studies. To frame the seminar content, a free background seminar is provided when enrolling: Longitudinal SEM in R. An official Instats certificate of completion is provided at the conclusion of the seminar. The seminar offers 2 ECTS Equivalent points for European PhD students.
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Nasr, Elhami, Tariq Shehab, Nigel Blampied, and Vinit Kanani. Estimating Models for Engineering Costs on the State Highway Operation and Protection Program (SHOPP) Portfolio of Projects. Mineta Transportation Institute, 2024. http://dx.doi.org/10.31979/mti.2024.2365.

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The State Highway Operation and Protection Program (SHOPP) is crucial for maintaining California’s 15,000-mile state highway system, which includes projects like pavement rehabilitation, bridge repair, safety enhancements, and traffic management systems. Administered by Caltrans, SHOPP aims to preserve highway efficiency and safety, supporting economic growth and public safety. This research aimed to develop robust cost-estimating models to improve budgeting and financial planning, aiding Caltrans, the California Transportation Commission (CTC), and the Legislature. The research team collected and refined comprehensive data from Caltrans project expenditures from 1983 to 2021, ensuring a high-quality dataset. Subject matter experts validated the data, enhancing its reliability. Two models were developed: a statistical model using exponential regression to account for non-linear cost growth, and an AI model employing neural networks to handle complex relationships in the data. Model performance was evaluated based on accuracy and reliability through repeated testing and validation. Key findings indicated that the new models significantly improved the precision of cost forecasts, reducing the variance between predicted and actual project costs. This advancement minimizes budget overruns and enhances resource allocation efficiency. Additionally, leveraging historical data with current market trends refined the models’ predictive power, boosting stakeholder confidence in project budgeting and financial planning. The study’s innovative approach, integrating machine learning and big data analytics, transforms traditional estimation practices and serves as a reference for other state highway programs. Continuous improvement and broader application of these models are recommended to further enhance cost estimation accuracy and support informed decision-making in transportation infrastructure management.
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Layne, Jeffery, and Scott Weaver. A Continuum of Models for Stochastic Estimation. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada387984.

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Ziesler, Pamela, and James Horn. Statistical abstract: 2024. National Park Service, 2025. https://doi.org/10.36967/2310175.

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In the pages that follow, a series of tables and figures display visitor use statistics for calendar year 2024. By documenting visits, hours, and overnight stays across the National Park System, the National Park Service (NPS) Statistical Abstract offers a historical record of visitor use in parks and provides NPS staff and partners with a useful tool for effective management and planning. In 2024, 404 of 433 National Park System units collected and reported visitor use statistics; the remainder are unable to do so for a variety of reasons such as administration by another agency, non-federal land ownership, or new parks that lack staff and facilities for the management of visitor use statistics. The responsibility for compiling and summarizing visitor use statistics resides with the Socioeconomic and Resource Recovery Division in the Natural Resource Stewardship and Science Directorate. The Division relies on the conscientious efforts of NPS field personnel to count, record, and report visitor use. This system of collecting and summarizing monthly visitor use data is combined with continuous review and assessment of park visitor use estimation procedures to promote consistency and accuracy of data. Detailed instructions for the units that collect data, monthly visitation summaries, and reports displaying trends in park visitation are available on the NPS Visitor Use Statistics website.
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Ziesler, Pamela, and Claire Spalding. Statistical abstract: 2023. National Park Service, 2024. http://dx.doi.org/10.36967/2304344.

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In the pages that follow, a series of tables and figures display visitor use statistics for calendar year 2023. By documenting visits, hours, and overnight stays across the National Park System, the National Park Service (NPS) Statistical Abstract offers a historical record of visitor use in parks and provides NPS staff and partners with a useful tool for effective management and planning. In 2023, 400 of the 428 National Park System units collected and reported visitor use statistics; the remainder are unable to do so for a variety of reasons such as administration by another agency, non-federal land ownership, or new parks that lack staff and facilities for the management of visitor use statistics. The responsibility for compiling and summarizing visitor use statistics resides with the Social Science Program in the NPS Natural Resource Stewardship and Science Directorate. The Program relies on the conscientious efforts of NPS field personnel to count, record, and report visitor use. This system of collecting and summarizing monthly visitor use data is combined with continuous review and assessment of park visitor use estimation procedures to promote consistency and accuracy of data. Detailed instructions for the units that collect data, monthly visitation summaries, and reports displaying trends in park visitation are available on the NPS Visitor Use Statistics website (https://irma.nps.gov/Stats/)
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