Journal articles: 'Continuous estimation'

1

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

2

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

3

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

4

Xu, Ke-Li. "REWEIGHTED FUNCTIONAL ESTIMATION OF DIFFUSION MODELS." Econometric Theory 26, no. 2 (2009): 541–63. http://dx.doi.org/10.1017/s0266466609100087.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

5

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

6

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

7

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

8

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

9

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.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

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.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Gianani, Ilaria, and Claudia Benedetti. "Multiparameter estimation of continuous-time quantum walk Hamiltonians through machine learning." AVS Quantum Science 5, no. 1 (2023): 014405. http://dx.doi.org/10.1116/5.0137398.

Full text

Abstract:

The characterization of the Hamiltonian parameters defining a quantum walk is of paramount importance when performing a variety of tasks, from quantum communication to computation. When dealing with physical implementations of quantum walks, the parameters themselves may not be directly accessible, and, thus, it is necessary to find alternative estimation strategies exploiting other observables. Here, we perform the multiparameter estimation of the Hamiltonian parameters characterizing a continuous-time quantum walk over a line graph with n-neighbor interactions using a deep neural network model fed with experimental probabilities at a given evolution time. We compare our results with the bounds derived from estimation theory and find that the neural network acts as a nearly optimal estimator both when the estimation of two or three parameters is performed.

APA, Harvard, Vancouver, ISO, and other styles

12

Dunovic, Ivana Burcar, Kristijan Robert Prebanic, and Pavao Durrigl. "Method for Base Estimation of Construction Time for Linear Projects in Front-end Project Phases." Organization, Technology and Management in Construction: an International Journal 12, no. 2 (2020): 2312–26. http://dx.doi.org/10.2478/otmcj-2018-0026.

Full text

Abstract:

AbstractEven though horizontally linear projects have low complexity schedules, they are still not successful in meeting planned time. The deadlines are mostly based on estimations done in front-end project development when limited data are available. Early time estimation models in literature rely on few variables and, almost in all cases, one of them is the estimated cost. Early cost estimations can significantly deviate from actual costs and thus lead to unreliable time estimation. Time estimation models based on neural network and other alternative methods require databases and software, which complicates the process of time estimation. The purpose of this paper is to bridge the gap of scarce time estimation models and unreliable time estimates by developing a new method for time estimation. This research has been done on one large sewer system project. The case study shows how to extract several continuous activities for a pipeline project chosen from a sewer system. Moreover, a new algorithm for the calculation of project duration is devised based on the existing equation related to the linear scheduling method, and this algorithm works with continuous activities. The new method for construction time estimation is based on the extraction of linear continuous activities, usage of the algorithm for identification of minimal buffer between activities, and calculation of the project duration. To verify the algorithm, this method is used on another pipeline project from a sewer system. The limitation is that this method can be used only for base estimation. Further research needs to be done to include uncertainties and risks in the method.

APA, Harvard, Vancouver, ISO, and other styles

13

Bidabad, Bijan. "Estimating Lorenz Curve for Iran by Using Continuous L1 Norm Estimation." International Journal of Marketing Research Innovation 3, no. 1 (2019): 11–21. http://dx.doi.org/10.46281/ijmri.v3i1.322.

Full text

Abstract:

In this paper, the L1 norm of continuous functions and corresponding continuous estimation of regression parameters are defined. The continuous L1 norm estimation problem of one and two parameters linear models in the continuous case are solved. We proceed to use the functional form and parameters of the probability distribution function of income to exactly determine the L1 norm approximation of the corresponding Lorenz curve of the statistical population under consideration. Iran family budget data were used to estimate income distribution for the period of 1362-1370.

APA, Harvard, Vancouver, ISO, and other styles

14

Li, Xiaoou, and Gongjun Xu. "Uniformly efficient simulation for extremes of Gaussian random fields." Journal of Applied Probability 55, no. 1 (2018): 157–78. http://dx.doi.org/10.1017/jpr.2018.11.

Full text

Abstract:

AbstractIn this paper we consider the problem of simultaneously estimating rare-event probabilities for a class of Gaussian random fields. A conventional rare-event simulation method is usually tailored to a specific rare event and consequently would lose estimation efficiency for different events of interest, which often results in additional computational cost in such simultaneous estimation problems. To overcome this issue, we propose a uniformly efficient estimator for a general family of Hölder continuous Gaussian random fields. We establish the asymptotic and uniform efficiency of the proposed method and also conduct simulation studies to illustrate its effectiveness.

APA, Harvard, Vancouver, ISO, and other styles

15

Archibald, Christopher, and Delma Nieves-Rivera. "Estimating Agent Skill in Continuous Action Domains." Journal of Artificial Intelligence Research 80 (May 10, 2024): 27–86. http://dx.doi.org/10.1613/jair.1.15326.

Full text

Abstract:

Actions in most real-world continuous domains cannot be executed exactly. An agent’s performance in these domains is influenced by two critical factors: the ability to select effective actions (decision-making skill), and how precisely it can execute those selected actions (execution skill). This article addresses the problem of estimating the execution and decision-making skill of an agent, given observations. Several execution skill estimation methods are presented, each of which utilize different information from the observations and make assumptions about the agent’s decision-making ability. A final novel method forgoes these assumptions about decision-making and instead estimates the execution and decision-making skills simultaneously under a single Bayesian framework. Experimental results in several domains evaluate the estimation accuracy of the estimators, especially focusing on how robust they are as agents and their decision-making methods are varied. These results demonstrate that reasoning about both types of skill together significantly improves the robustness and accuracy of execution skill estimation. A case study is presented using the proposed methods to estimate the skill of Major League Baseball pitchers, demonstrating how these methods can be applied to real-world data sources.

APA, Harvard, Vancouver, ISO, and other styles

16

Kowalczuk, Zdzisław, and Mariusz Domżalski. "Asynchronous distributed state estimation for continuous-time stochastic processes." International Journal of Applied Mathematics and Computer Science 23, no. 2 (2013): 327–39. http://dx.doi.org/10.2478/amcs-2013-0025.

Full text

Abstract:

The problem of state estimation of a continuous-time stochastic process using an Asynchronous Distributed multi-sensor Estimation (ADE) system is considered. The state of a process of interest is estimated by a group of local estimators constituting the proposed ADE system. Each estimator is based, e.g., on a Kalman filter and performs single sensor filtration and fusion of its local results with the results from other/remote processors to compute possibly the best state estimates. In performing data fusion, however, two important issues need to be addressed namely, the problem of asynchronism of local processors and the issue of unknown correlation between asynchronous data in local processors. Both the problems, along with their solutions, are investigated in this paper. Possible applications and effectiveness of the proposed ADE approach are illustrated by simulated experiments, including a non-complete connection graph of such a distributed estimation system.

APA, Harvard, Vancouver, ISO, and other styles

17

Hosoda, Shion, Tsukasa Fukunaga, and Michiaki Hamada. "Umibato: estimation of time-varying microbial interaction using continuous-time regression hidden Markov model." Bioinformatics 37, Supplement_1 (2021): i16—i24. http://dx.doi.org/10.1093/bioinformatics/btab287.

Full text

Abstract:

Abstract Motivation Accumulating evidence has highlighted the importance of microbial interaction networks. Methods have been developed for estimating microbial interaction networks, of which the generalized Lotka–Volterra equation (gLVE)-based method can estimate a directed interaction network. The previous gLVE-based method for estimating microbial interaction networks did not consider time-varying interactions. Results In this study, we developed unsupervised learning-based microbial interaction inference method using Bayesian estimation (Umibato), a method for estimating time-varying microbial interactions. The Umibato algorithm comprises Gaussian process regression (GPR) and a new Bayesian probabilistic model, the continuous-time regression hidden Markov model (CTRHMM). Growth rates are estimated by GPR, and interaction networks are estimated by CTRHMM. CTRHMM can estimate time-varying interaction networks using interaction states, which are defined as hidden variables. Umibato outperformed the existing methods on synthetic datasets. In addition, it yielded reasonable estimations in experiments on a mouse gut microbiota dataset, thus providing novel insights into the relationship between consumed diets and the gut microbiota. Availability and implementation The C++ and python source codes of the Umibato software are available at https://github.com/shion-h/Umibato. Supplementary information Supplementary data are available at Bioinformatics online.

APA, Harvard, Vancouver, ISO, and other styles

18

Nowman, K. Ben. "Open Higher Order Continuous-Time Dynamic Model with Mixed Stock and Flow Data and Derivatives of Exogenous Variables." Econometric Theory 7, no. 3 (1991): 404–8. http://dx.doi.org/10.1017/s0266466600004540.

Full text

Abstract:

This paper is concerned with deriving formulae for higher order derivatives of exogenous variables for use in estimating the parameters of an open secondorder continuous time model with mixed stock and flow data and first and second order derivatives of exogenous variables which are not observable. This should provide the basis for the future estimation of continuous time models in a range of applied areas using the new Gaussian estimation computer program developed by Nowman [4].

APA, Harvard, Vancouver, ISO, and other styles

19

Hönekopp, Johannes, and Audrey Helen Linden. "Heterogeneity estimates in a biased world." PLOS ONE 17, no. 2 (2022): e0262809. http://dx.doi.org/10.1371/journal.pone.0262809.

Full text

Abstract:

Meta-analyses typically quantify heterogeneity of results, thus providing information about the consistency of the investigated effect across studies. Numerous heterogeneity estimators have been devised. Past evaluations of their performance typically presumed lack of bias in the set of studies being meta-analysed, which is often unrealistic. The present study used computer simulations to evaluate five heterogeneity estimators under a range of research conditions broadly representative of meta-analyses in psychology, with the aim to assess the impact of biases in sets of primary studies on estimates of both mean effect size and heterogeneity in meta-analyses of continuous outcome measures. To this end, six orthogonal design factors were manipulated: Strength of publication bias; 1-tailed vs. 2-tailed publication bias; prevalence of p-hacking; true heterogeneity of the effect studied; true average size of the studied effect; and number of studies per meta-analysis. Our results showed that biases in sets of primary studies caused much greater problems for the estimation of effect size than for the estimation of heterogeneity. For the latter, estimation bias remained small or moderate under most circumstances. Effect size estimations remained virtually unaffected by the choice of heterogeneity estimator. For heterogeneity estimates, however, relevant differences emerged. For unbiased primary studies, the REML estimator and (to a lesser extent) the Paule-Mandel performed well in terms of bias and variance. In biased sets of primary studies however, the Paule-Mandel estimator performed poorly, whereas the DerSimonian-Laird estimator and (to a slightly lesser extent) the REML estimator performed well. The complexity of results notwithstanding, we suggest that the REML estimator remains a good choice for meta-analyses of continuous outcome measures across varied circumstances.

APA, Harvard, Vancouver, ISO, and other styles

20

Kuś*, Rafał, Katarzyna Blinowska, Maciej Kamiński, and Anna Basińska-Starzycka. "Transmission of information during Continuous Attention Test." Acta Neurobiologiae Experimentalis 68, no. 1 (2008): 103–12. http://dx.doi.org/10.55782/ane-2008-1678.

Full text

Abstract:

The Short-Time Directed Transfer Function (SDTF) is an estimator based on a multivariate autoregressive model which has proved to be successful in ERP experiments, e.g. those connected with motor action and its imagination. The aim of this study is the evaluation of the performance of SDTF in the cognitive experiment. We have applied SDTF for the estimation of the pattern of EEG signal transmissions during a Continuous Attention Test (CAT). Time-frequency patterns of propagation were estimated for two experimental conditions. Statistical procedures based on thin-plate spline model were used for estimation of significant changes in respect to the reference epoch. The repeatability of the results for a subject and across the subjects were investigated. The effect of prolonged transmission in the gamma band from the prefrontal electrodes found in all subjects was explained by the active inhibition in the case when a subject had to sustain from performing the action.

APA, Harvard, Vancouver, ISO, and other styles

21

Garner, Philip N., Milos Cernak, and Petr Motlicek. "A Simple Continuous Pitch Estimation Algorithm." IEEE Signal Processing Letters 20, no. 1 (2013): 102–5. http://dx.doi.org/10.1109/lsp.2012.2231675.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Pinton, Gianmarco, and Gregg Trahey. "Continuous delay estimation with polynomial splines." IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 53, no. 11 (2006): 2026–35. http://dx.doi.org/10.1109/tuffc.2006.143.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

VETTER, MATHIAS. "Estimation of Correlation for Continuous Semimartingales." Scandinavian Journal of Statistics 39, no. 4 (2012): 757–71. http://dx.doi.org/10.1111/j.1467-9469.2012.00783.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Gerencs�r, L�szl�, and Zsuzsanna V�g�. "Fixed-gain estimation in continuous time." Acta Applicandae Mathematicae 35, no. 1-2 (1994): 153–64. http://dx.doi.org/10.1007/bf00994915.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Pinton, Gianmarco, and Gregg Trahey. "Continuous delay estimation with polynomial splines." Journal of the Acoustical Society of America 120, no. 5 (2006): 3112. http://dx.doi.org/10.1121/1.4787607.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Karshenas, Hossein, Roberto Santana, Concha Bielza, and Pedro Larrañaga. "Regularized continuous estimation of distribution algorithms." Applied Soft Computing 13, no. 5 (2013): 2412–32. http://dx.doi.org/10.1016/j.asoc.2012.11.049.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

CHOU, JYH-HORNG, and ING-RONG HORNG. "State estimation using continuous orthogonal functions." International Journal of Systems Science 17, no. 9 (1986): 1261–67. http://dx.doi.org/10.1080/00207728608926885.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Gagnon, Louise, and J. F. Macgregor. "State estimation for continuous emulsion polymerization." Canadian Journal of Chemical Engineering 69, no. 3 (1991): 648–56. http://dx.doi.org/10.1002/cjce.5450690307.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Ding, Rui, та Andrew Mullhaupt. "Empirical Squared Hellinger Distance Estimator and Generalizations to a Family of α-Divergence Estimators". Entropy 25, № 4 (2023): 612. http://dx.doi.org/10.3390/e25040612.

Full text

Abstract:

We present an empirical estimator for the squared Hellinger distance between two continuous distributions, which almost surely converges. We show that the divergence estimation problem can be solved directly using the empirical CDF and does not need the intermediate step of estimating the densities. We illustrate the proposed estimator on several one-dimensional probability distributions. Finally, we extend the estimator to a family of estimators for the family of α-divergences, which almost surely converge as well, and discuss the uniqueness of this result. We demonstrate applications of the proposed Hellinger affinity estimators to approximately bounding the Neyman–Pearson regions.

APA, Harvard, Vancouver, ISO, and other styles

30

Bonat, Wagner H., Ricardo R. Petterle, John Hinde, and Clarice GB Demétrio. "Flexible quasi-beta regression models for continuous bounded data." Statistical Modelling 19, no. 6 (2018): 617–33. http://dx.doi.org/10.1177/1471082x18790847.

Full text

Abstract:

We propose a flexible class of regression models for continuous bounded data based on second-moment assumptions. The mean structure is modelled by means of a link function and a linear predictor, while the mean and variance relationship has the form [Formula: see text], where [Formula: see text], [Formula: see text] and [Formula: see text] are the mean, dispersion and power parameters respectively. The models are fitted by using an estimating function approach where the quasi-score and Pearson estimating functions are employed for the estimation of the regression and dispersion parameters respectively. The flexible quasi-beta regression model can automatically adapt to the underlying bounded data distribution by the estimation of the power parameter. Furthermore, the model can easily handle data with exact zeroes and ones in a unified way and has the Bernoulli mean and variance relationship as a limiting case. The computational implementation of the proposed model is fast, relying on a simple Newton scoring algorithm. Simulation studies, using datasets generated from simplex and beta regression models show that the estimating function estimators are unbiased and consistent for the regression coefficients. We illustrate the flexibility of the quasi-beta regression model to deal with bounded data with two examples. We provide an R implementation and the datasets as supplementary materials.

APA, Harvard, Vancouver, ISO, and other styles

31

Sankaranarayanan, Manipriya, Mala C., and Samson Mathew. "Road Traffic Congestion (TraCo) Estimation Using Multi-Layer Continuous Virtual Loop (MCVL)." International Journal of Intelligent Information Technologies 17, no. 2 (2021): 46–71. http://dx.doi.org/10.4018/ijiit.2021040103.

Full text

Abstract:

Any road traffic management application of intelligent transportation systems (ITS) requires traffic characteristics data such as vehicle density, speed, etc. This paper proposes a robust and novel vehicle detection framework known as multi-layer continuous virtual loop (MCVL) that uses computer vision techniques on road traffic video to estimate traffic characteristics. Estimations of traffic data such as speed, area occupancy and an exclusive spatial feature named as corner detail value (CDV) acquired using MCVL are proposed. Further, the estimation of traffic congestion (TraCo) level using these parameters is also presented. The performances of the entire framework and TraCo estimation are evaluated using several benchmark traffic video datasets and the results are presented. The results show that the improved accuracy in vehicle detection process using MCVL subsequently improves the precision of TraCo estimation. This also means that the proposed framework is well suited to applications that need traffic characteristics to update their traffic information system in real time.

APA, Harvard, Vancouver, ISO, and other styles

32

Li, Bicao, Guanyu Yang, Zhoufeng Liu, Jean Louis Coatrieux, and Huazhong Shu. "Multimodal Medical Image Registration Based on an Information-Theory Measure with Histogram Estimation of Continuous Image Representation." Mathematical Problems in Engineering 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/2135453.

Full text

Abstract:

This work presents a novel method for multimodal medical registration based on histogram estimation of continuous image representation. The proposed method, regarded as “fast continuous histogram estimation,” employs continuous image representation to estimate the joint histogram of two images to be registered. The Jensen–Arimoto (JA) divergence is a similarity measure to measure the statistical dependence between medical images from different modalities. The estimated joint histogram is exploited to calculate the JA divergence in multimodal medical image registration. In addition, to reduce the grid effect caused by the grid-aligning transformations between two images and improve the implementation speed of the registration method, random samples instead of all pixels are extracted from the images to be registered. The goal of the registration is to optimize the JA divergence, which would be maximal when two misregistered images are perfectly aligned using the downhill simplex method, and thus to get the optimal geometric transformation. Experiments are conducted on an affine registration of 2D and 3D medical images. Results demonstrate the superior performance of the proposed method compared to standard histogram, Parzen window estimations, particle filter, and histogram estimation based on continuous image representation without random sampling.

APA, Harvard, Vancouver, ISO, and other styles

33

Ai, Chunrong, Oliver Linton, Kaiji Motegi, and Zheng Zhang. "A unified framework for efficient estimation of general treatment models." Quantitative Economics 12, no. 3 (2021): 779–816. http://dx.doi.org/10.3982/qe1494.

Full text

Abstract:

This paper presents a weighted optimization framework that unifies the binary, multivalued, and continuous treatment—as well as mixture of discrete and continuous treatment—under a unconfounded treatment assignment. With a general loss function, the framework includes the average, quantile, and asymmetric least squares causal effect of treatment as special cases. For this general framework, we first derive the semiparametric efficiency bound for the causal effect of treatment, extending the existing bound results to a wider class of models. We then propose a generalized optimization estimator for the causal effect with weights estimated by solving an expanding set of equations. Under some sufficient conditions, we establish the consistency and asymptotic normality of the proposed estimator of the causal effect and show that the estimator attains the semiparametric efficiency bound, thereby extending the existing literature on efficient estimation of causal effect to a wider class of applications. Finally, we discuss estimation of some causal effect functionals such as the treatment effect curve and the average outcome. To evaluate the finite sample performance of the proposed procedure, we conduct a small‐scale simulation study and find that the proposed estimation has practical value. In an empirical application, we detect a significant causal effect of political advertisements on campaign contributions in the binary treatment model, but not in the continuous treatment model.

APA, Harvard, Vancouver, ISO, and other styles

34

Li, Changchun, Xinyan Li, Xiaopeng Meng, et al. "Hyperspectral Estimation of Nitrogen Content in Wheat Based on Fractional Difference and Continuous Wavelet Transform." Agriculture 13, no. 5 (2023): 1017. http://dx.doi.org/10.3390/agriculture13051017.

Full text

Abstract:

Nitrogen content is a crucial index for crop growth diagnosis and the exact estimation of nitrogen content is of great significance for grasping crop growth status in real-time. This paper takes winter wheat as the study object and the precision agriculture demonstration area of the Jiaozuo Academy of Agricultural and Forestry Sciences in Henan Province as the research area. The hyperspectral reflectance data of the wheat canopy in different growth periods are obtained with the ASD ground object hyperspectral instrument, and the original canopy spectral data are preprocessed by fractional differential and continuous wavelet transform; then, the vegetation indices are established, correlation analysis with nitrogen content is conducted, and the fractional differential spectra are selected; finally, based on the wavelet energy coefficient and the vegetation indices with strong correlations, the methods of support vector machine (SVM), ridge regression, stepwise regression, Gaussian process regression (GPR), and the BP neural network are used to construct the estimation model for nitrogen content in wheat at different growth stages. By adopting the R2 and root mean square error (RMSE) indices, the best nitrogen content estimation model at every growth stage is selected. The overall analysis of the nitrogen content estimation effect indicated that for the four growth periods, the maximum modeling and validation R2 of the nitrogen content estimation models of the SVM, ridge regression, stepwise regression, GPR, and BP neural network models reached 0.95 and 0.93, the average reached 0.76 and 0.71, and the overall estimation effect was good. The average values of the modeling and validation R2 of the nitrogen content estimation model at the flag picking stage were 0.85 and 0.81, respectively, which were 37.10% and 44.64%, 1.19% and 3.85%, and 14.86% and 17.39% higher than those at the jointing stage, flowering stage, and filling stage, respectively. Therefore, the model of the flag picking stage has higher estimation accuracy and a better estimation effect on the nitrogen content. For the different growth stages, the optimal estimation models of nitrogen content were different. Among them, continuous wavelet transform combined with the BP neural network model can be the most effective method for estimating the N content in wheat at the flagging stage. The paper provides an effective method for estimating the nitrogen content in wheat and a new idea for crop growth monitoring.

APA, Harvard, Vancouver, ISO, and other styles

35

Marzen, Sarah E., and James P. Crutchfield. "Inference, Prediction, & Entropy-Rate Estimation of Continuous-Time, Discrete-Event Processes." Entropy 24, no. 11 (2022): 1675. http://dx.doi.org/10.3390/e24111675.

Full text

Abstract:

Inferring models, predicting the future, and estimating the entropy rate of discrete-time, discrete-event processes is well-worn ground. However, a much broader class of discrete-event processes operates in continuous-time. Here, we provide new methods for inferring, predicting, and estimating them. The methods rely on an extension of Bayesian structural inference that takes advantage of neural network’s universal approximation power. Based on experiments with complex synthetic data, the methods are competitive with the state-of-the-art for prediction and entropy-rate estimation.

APA, Harvard, Vancouver, ISO, and other styles

36

Bolancé, Catalina, and Montserrat Guillen. "Nonparametric Estimation of Extreme Quantiles with an Application to Longevity Risk." Risks 9, no. 4 (2021): 77. http://dx.doi.org/10.3390/risks9040077.

Full text

Abstract:

A new method to estimate longevity risk based on the kernel estimation of the extreme quantiles of truncated age-at-death distributions is proposed. Its theoretical properties are presented and a simulation study is reported. The flexible yet accurate estimation of extreme quantiles of age-at-death conditional on having survived a certain age is fundamental for evaluating the risk of lifetime insurance. Our proposal combines a parametric distributions with nonparametric sample information, leading to obtain an asymptotic unbiased estimator of extreme quantiles for alternative distributions with different right tail shape, i.e., heavy tail or exponential tail. A method for estimating the longevity risk of a continuous temporary annuity is also shown. We illustrate our proposal with an application to the official age-at-death statistics of the population in Spain.

APA, Harvard, Vancouver, ISO, and other styles

37

VOSS, HENNING U., JENS TIMMER, and JÜRGEN KURTHS. "NONLINEAR DYNAMICAL SYSTEM IDENTIFICATION FROM UNCERTAIN AND INDIRECT MEASUREMENTS." International Journal of Bifurcation and Chaos 14, no. 06 (2004): 1905–33. http://dx.doi.org/10.1142/s0218127404010345.

Full text

Abstract:

We review the problem of estimating parameters and unobserved trajectory components from noisy time series measurements of continuous nonlinear dynamical systems. It is first shown that in parameter estimation techniques that do not take the measurement errors explicitly into account, like regression approaches, noisy measurements can produce inaccurate parameter estimates. Another problem is that for chaotic systems the cost functions that have to be minimized to estimate states and parameters are so complex that common optimization routines may fail. We show that the inclusion of information about the time-continuous nature of the underlying trajectories can improve parameter estimation considerably. Two approaches, which take into account both the errors-in-variables problem and the problem of complex cost functions, are described in detail: shooting approaches and recursive estimation techniques. Both are demonstrated on numerical examples.

APA, Harvard, Vancouver, ISO, and other styles

38

Luong, Andrew. "Robust Continuous Quadratic Distance Estimation Using Quantiles for Fitting Continuous Distributions." Open Journal of Statistics 09, no. 04 (2019): 421–35. http://dx.doi.org/10.4236/ojs.2019.94028.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Bensaker, B. "Continuous-Time System Monitoring via a Continuous-Time Model Parameter Estimation." IFAC Proceedings Volumes 33, no. 17 (2000): 1117–21. http://dx.doi.org/10.1016/s1474-6670(17)39561-7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

SUNIL KUMAR SUVVARI, DR. ROHINI SAWALKAR, and DR. VISHWANATH KARAD. "The Effect of Team Size and Dynamics on Agile Estimation." Innovative Research Thoughts 9, no. 5 (2023): 178–87. http://dx.doi.org/10.36676/irt.v9.i5.1478.

Full text

Abstract:

This paper presents the impact of team size and dynamics on agile estimation accuracy and strategies for improving estimation in diversified teams. We employed a mixed-method approach with online surveys, interviews, and case studies. The data received and analyzed in this research came from 150 agile teams representing different industries. Our results show that strong interdependency exists between team size and the dispersion of estimations. The best estimation accuracy was when the team had 5-9 members. Team dynamics, particularly cohesion and psychological safety, emerged as important in the estimation outcome. Based on these insights, we propose a framework for improving estimation practice within agile teams, including tailoring and continuous improvement.

APA, Harvard, Vancouver, ISO, and other styles

41

Bidabad, Bijan. "Continuous L1 Norm Estimation of Lorenz Curve." Bangladesh Journal of Multidisciplinary Scientific Research 1, no. 1 (2019): 41–49. http://dx.doi.org/10.46281/bjmsr.v1i1.314.

Full text

Abstract:

In this paper, the L1 norm of continuous functions and corresponding continuous estimation of regression parameters are defined. The continuous L1 norm estimation problem of one and two parameters linear models in the continuous case is solved. We proceed to use the functional form and parameters of the probability distribution function of income to exactly determine the L1 norm approximation of the corresponding Lorenz curve of the statistical population under consideration. 

APA, Harvard, Vancouver, ISO, and other styles

42

Cameron, D., K. Beven, J. Tawn, and P. Naden. "Flood frequency estimation by continuous simulation (with likelihood based uncertainty estimation)." Hydrology and Earth System Sciences 4, no. 1 (2000): 23–34. http://dx.doi.org/10.5194/hess-4-23-2000.

Full text

Abstract:

Abstract. A continuous simulation methodology, which incorporates the quantification of modelling uncertainties, is used for flood frequency estimation. The methodology utilises the rainfall-runoff model TOPMODEL within the uncertainty framework of GLUE. Long return period estimates are obtained through the coupling of a stochastic rainfall generator with TOPMODEL. Examples of applications to four gauged UK catchments are provided. A comparison with a traditional statistical approach indicates the suitability of the methodology as an alternative technique for flood frequency estimation. It is suggested that, given an appropriate choice of rainfall-runoff model and stochastic rainstorm generator, the basic methodology can be adapted for use in many other regions of the world. Keywords: Floods; Frequency; TOPMODEL; Rainfall-runoff modelling

APA, Harvard, Vancouver, ISO, and other styles

43

Shu, Di, and Grace Y. Yi. "Causal inference with measurement error in outcomes: Bias analysis and estimation methods." Statistical Methods in Medical Research 28, no. 7 (2017): 2049–68. http://dx.doi.org/10.1177/0962280217743777.

Full text

Abstract:

Inverse probability weighting estimation has been popularly used to consistently estimate the average treatment effect. Its validity, however, is challenged by the presence of error-prone variables. In this paper, we explore the inverse probability weighting estimation with mismeasured outcome variables. We study the impact of measurement error for both continuous and discrete outcome variables and reveal interesting consequences of the naive analysis which ignores measurement error. When a continuous outcome variable is mismeasured under an additive measurement error model, the naive analysis may still yield a consistent estimator; when the outcome is binary, we derive the asymptotic bias in a closed-form. Furthermore, we develop consistent estimation procedures for practical scenarios where either validation data or replicates are available. With validation data, we propose an efficient method for estimation of average treatment effect; the efficiency gain is substantial relative to usual methods of using validation data. To provide protection against model misspecification, we further propose a doubly robust estimator which is consistent even when either the treatment model or the outcome model is misspecified. Simulation studies are reported to assess the performance of the proposed methods. An application to a smoking cessation dataset is presented.

APA, Harvard, Vancouver, ISO, and other styles

44

Witkovský, Viktor, Gejza Wimmer, and Tomas Duby. "Estimating the distribution of a stochastic sum of IID random variables." Mathematica Slovaca 70, no. 3 (2020): 759–74. http://dx.doi.org/10.1515/ms-2017-0389.

Full text

Abstract:

AbstractSuggested is a non-parametric method and algorithm for estimating the probability distribution of a stochastic sum of independent identically distributed continuous random variables, based on combining and numerically inverting the associated empirical characteristic function (CF) derived from the observed data. This is motivated by classical problems in financial risk management, actuarial science, and hydrological modelling. This approach can be naturally generalized to more complex semi-parametric modelling and estimating approaches, e.g., by incorporating the generalized Pareto distribution fit for modelling heavy tails of the considered continuous random variables, or by considering the weighted mixture of the parametric CFs (used to incorporate the expert knowledge) and the empirical CFs (used to incorporate the knowledge based on the observed or historical data). The suggested numerical approach is based on combination of the Gil-Pelaez inversion formulae for deriving the probability distribution (PDF and CDF) from the associated CF and the trapezoidal quadrature rule used for the required numerical integration. The presented non-parametric estimation method is related to the bootstrap estimation approach, and thus, it shares similar properties. Applicability of the proposed estimation procedure is illustrated by estimating the aggregate loss distribution from the well-known Danish fire losses data.

APA, Harvard, Vancouver, ISO, and other styles

45

Benson, David, Matthew A. Masten, and Alexander Torgovitsky. "ivcrc: An instrumental-variables estimator for the correlated random-coefficients model." Stata Journal: Promoting communications on statistics and Stata 22, no. 3 (2022): 469–95. http://dx.doi.org/10.1177/1536867x221124449.

Full text

Abstract:

We discuss the ivcrc command, which implements an instrumental-variables (IV) estimator for the linear correlated random-coefficients model. The correlated random-coefficients model is a natural generalization of the standard linear IV model that allows for endogenous, multivalued treatments and unobserved heterogeneity in treatment effects. The estimator implemented by ivcrc uses recent semiparametric identification results that allow for flexible functional forms and permit instruments that may be binary, discrete, or continuous. The ivcrc command also allows for the estimation of varying-coefficient regressions, which are closely related in structure to the proposed IV estimator. We illustrate the use of ivcrc by estimating the returns to education in the National Longitudinal Survey of Young Men.

APA, Harvard, Vancouver, ISO, and other styles

46

Benson, David, Matthew A. Masten, and Alexander Torgovitsky. "ivcrc: An Instrumental Variables Estimator for the Correlated Random Coefficients Model." Finance and Economics Discussion Series 2020, no. 046r1 (2022): 1–29. http://dx.doi.org/10.17016/feds.2020.046r1.

Full text

Abstract:

We discuss the ivcrc module, which implements an instrumental variables (IV) estimator for the linear correlated random coefficients (CRC) model. The CRC model is a natural generalization of the standard linear IV model that allows for endogenous, multivalued treatments and unobserved heterogeneity in treatment effects. The estimator implemented by ivcrc uses recent semiparametric identification results that allow for flexible functional forms and permit instruments that may be binary, discrete, or continuous. The ivcrc module also allows for the estimation of varying coefficients regressions, which are closely related in structure to the proposed IV estimator. We illustrate use of ivcrc by estimating the returns to education in the National Longitudinal Survey of Young Men.

APA, Harvard, Vancouver, ISO, and other styles

47

Wodtke, Geoffrey T. "Regression-based Adjustment for Time-varying Confounders." Sociological Methods & Research 49, no. 4 (2018): 906–46. http://dx.doi.org/10.1177/0049124118769087.

Full text

Abstract:

Social scientists are often interested in estimating the marginal effects of a time-varying treatment on an end-of-study continuous outcome. With observational data, estimating these effects is complicated by the presence of time-varying confounders affected by prior treatments, which may lead to bias in conventional regression and matching estimators. In this situation, inverse-probability-of-treatment-weighted (IPTW) estimation of a marginal structural model remains unbiased if treatment assignment is sequentially ignorable and the conditional probability of treatment is correctly modeled, but this method is not without limitations. In particular, it is difficult to use with continuous treatments, and it is relatively inefficient. This article explores using an alternative regression-based method—regression-with-residuals (RWR) estimation of a constrained structural nested mean model—that may overcome some of these limitations in practice. It is unbiased for the marginal effects of a time-varying treatment if treatment assignment is sequentially ignorable, the treatment effects of interest are invariant across levels of the confounders, and a model for the conditional mean of the outcome is correctly specified. The performance of RWR estimation relative to IPTW estimation is evaluated with a series of simulation experiments and with an empirical example based on longitudinal data from the Panel Study of Income Dynamics. Results indicate that it may outperform IPTW estimation in certain situations.

APA, Harvard, Vancouver, ISO, and other styles

48

NISHIGUCHI, Kenichi, and Kazuo TSUCHIYA. "On Adaptive Estimation Algorithms in Continuous Time." Transactions of the Society of Instrument and Control Engineers 23, no. 9 (1987): 912–19. http://dx.doi.org/10.9746/sicetr1965.23.912.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Morelli, Davide, Alessio Rossi, Leonardo Bartoloni, Massimo Cairo, and David A. Clifton. "SDNN24 Estimation from Semi-Continuous HR Measures." Sensors 21, no. 4 (2021): 1463. http://dx.doi.org/10.3390/s21041463.

Full text

Abstract:

The standard deviation of the interval between QRS complexes recorded over 24 h (SDNN24) is an important metric of cardiovascular health. Wrist-worn fitness wearable devices record heart beats 24/7 having a complete overview of users’ heart status. Due to motion artefacts affecting QRS complexes recording, and the different nature of the heart rate sensor used on wearable devices compared to ECG, traditionally used to compute SDNN24, the estimation of this important Heart Rate Variability (HRV) metric has never been performed from wearable data. We propose an innovative approach to estimate SDNN24 only exploiting the Heart Rate (HR) that is normally available on wearable fitness trackers and less affected by data noise. The standard deviation of inter-beats intervals (SDNN24) and the standard deviation of the Average inter-beats intervals (ANN) derived from the HR (obtained in a time window with defined duration, i.e., 1, 5, 10, 30 and 60 min), i.e., ANN=60HR (SDANNHR24), were calculated over 24 h. Power spectrum analysis using the Lomb-Scargle Peridogram was performed to assess frequency domain HRV parameters (Ultra Low Frequency, Very Low Frequency, Low Frequency, and High Frequency). Due to the fact that SDNN24 reflects the total power of the power of the HRV spectrum, the values estimated from HR measures (SDANNHR24) underestimate the real values because of the high frequencies that are missing. Subjects with low and high cardiovascular risk show different power spectra. In particular, differences are detected in Ultra Low and Very Low frequencies, while similar results are shown in Low and High frequencies. For this reason, we found that HR measures contain enough information to discriminate cardiovascular risk. Semi-continuous measures of HR throughout 24 h, as measured by most wrist-worn fitness wearable devices, should be sufficient to estimate SDNN24 and cardiovascular risk.

APA, Harvard, Vancouver, ISO, and other styles

50

KIM, Woosuk, Hideaki KUZUOKA, and Kenji SUZUKI. "Online Continuous Scale Estimation of Hand Gestures." IEICE Transactions on Information and Systems E95.D, no. 10 (2012): 2447–55. http://dx.doi.org/10.1587/transinf.e95.d.2447.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Continuous estimation'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles