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Articoli di riviste sul tema "Moments Models"

Autore: Grafiati

Pubblicato: 25 gennaio 2025

Ultima modifica: 31 luglio 2025

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1

Hunana, P., T. Passot, E. Khomenko, et al. "Generalized Fluid Models of the Braginskii Type." Astrophysical Journal Supplement Series 260, no. 2 (2022): 26. http://dx.doi.org/10.3847/1538-4365/ac5044.

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Abstract Several generalizations of the well-known fluid model of Braginskii (1965) are considered. We use the Landau collisional operator and the moment method of Grad. We focus on the 21-moment model that is analogous to the Braginskii model, and we also consider a 22-moment model. Both models are formulated for general multispecies plasmas with arbitrary masses and temperatures, where all of the fluid moments are described by their evolution equations. The 21-moment model contains two “heat flux vectors” (third- and fifth-order moments) and two “viscosity tensors” (second- and fourth-order

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2

Hu, Zhicheng, Ruo Li, and Zhonghua Qiao. "Extended Hydrodynamic Models and Multigrid Solver of a Silicon Diode Simulation." Communications in Computational Physics 20, no. 3 (2016): 551–82. http://dx.doi.org/10.4208/cicp.290615.020316a.

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AbstractExtended hydrodynamic models for carrier transport are derived from the semiconductor Boltzmann equation with relaxation time approximation of the scattering term, by using the globally hyperbolic moment method and the moment-dependent relaxation time. Incorporating the microscopic relaxation time and the applied voltage bias, a formula is proposed to determine the relaxation time for each moment equation, which sets different relaxation rates for different moments such that higher moments damp faster. The resulting models would give more satisfactory results of macroscopic quantities

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3

Xiao, Zhiguo. "The weighted method of moments approach for moment condition models." Economics Letters 107, no. 2 (2010): 183–86. http://dx.doi.org/10.1016/j.econlet.2010.01.019.

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4

Hu, Yi, Xiaohua Xia, Ying Deng, and Dongmei Guo. "Higher Order Mean Squared Error of Generalized Method of Moments Estimators for Nonlinear Models." Discrete Dynamics in Nature and Society 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/324904.

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Generalized method of moments (GMM) has been widely applied for estimation of nonlinear models in economics and finance. Although generalized method of moments has good asymptotic properties under fairly moderate regularity conditions, its finite sample performance is not very well. In order to improve the finite sample performance of generalized method of moments estimators, this paper studies higher-order mean squared error of two-step efficient generalized method of moments estimators for nonlinear models. Specially, we consider a general nonlinear regression model with endogeneity and deri

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5

Petričková, Anna. "Moments of Markov-Switching Models." Tatra Mountains Mathematical Publications 61, no. 1 (2014): 131–40. http://dx.doi.org/10.2478/tmmp-2014-0032.

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Abstract In this paper we have focused on the class of regime-switching time series models with regimes determined by unobservable variables, concretely Markov-switching models. We have derived 2nd central moment of the MSW models for two cases-state-independent and state-dependent model

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6

Peck, Jamie, Nik Theodore, and Neil Brenner. "Neoliberal Urbanism: Models, Moments, Mutations." SAIS Review of International Affairs 29, no. 1 (2009): 49–66. http://dx.doi.org/10.1353/sais.0.0028.

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7

Amendola, Alessandra, Marcella Niglio, and Cosimo Vitale. "The moments of SETARMA models." Statistics & Probability Letters 76, no. 6 (2006): 625–33. http://dx.doi.org/10.1016/j.spl.2005.09.016.

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8

Timmermann, Allan. "Moments of Markov switching models." Journal of Econometrics 96, no. 1 (2000): 75–111. http://dx.doi.org/10.1016/s0304-4076(99)00051-2.

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9

Gasparutto, Xavier, Eric Jacquelin, and Raphael Dumas. "Contribution of passive actions to the lower limb joint moments and powers during gait: A comparison of models." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 232, no. 8 (2018): 768–78. http://dx.doi.org/10.1177/0954411918785661.

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The lower limb passive actions representing the actions of all the passive periarticular structures have been shown to have a significant contribution to the power generation and absorption during gait. However, the respective magnitude of its different components was not established, although models of ligament moment were implemented in some musculoskeletal models. These ligament moments have shown to have an influence on the musculo-tendon forces and contact forces but the models used were never specifically evaluated, that is, compared to the passive and net joint moments. Two models of pa

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10

Chen, Ming-Hua, and Zuu-Chang Hong. "A pdf Description of Turbulent Axisymmetric Free Jet Flow." Journal of Fluids Engineering 121, no. 1 (1999): 73–79. http://dx.doi.org/10.1115/1.2822015.

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This study presents the applications of a turbulence probability density function (pdf) equation to compute an axisymmetric turbulent free jet flow. In view of the difficulty of solving this pdf equation directly by conventional numerical methods, an approximate moment method is applied. The Calculated triple velocity correlations appearing in the second-order moments equation are calculated and compared with measured values and with those estimated by moment-closure models. The results reveal that the pdf approach gives consistency in the higher-order moments and radial budget of third moment

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11

Brekke, L. "Baryon Magnetic Moments in Quark Models with Anomalous Quark Moments." Annals of Physics 240, no. 2 (1995): 400–431. http://dx.doi.org/10.1006/aphy.1995.1050.

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12

Stirling, A. J., and J. A. Peacock. "Non-Gaussian Isocurvature Models." Symposium - International Astronomical Union 183 (1999): 268. http://dx.doi.org/10.1017/s0074180900132851.

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Peebles (1997) has proposed a non-Gaussian χ2isocurvature model which gives rise to early galaxy assembly at redshifts ≥ 3–4. We test whether the higher order moments (skewness and kurtosis) of such a model are compatible with the moments of the observed density field, and find that in the absence of bias these models produce moments that are much higher than those measured for the APM survey (Gaztañaga, 1994). We have applied different biasing schemes to see whether bias can bring the moments down, and find that for power law, Cen-Ostriker, and censor threshold biasing schemes (Mann et al 199

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13

Mat Jan, Nur Amalina, Ani Shabri, and Ruhaidah Samsudin. "Handling non-stationary flood frequency analysis using TL-moments approach for estimation parameter." Journal of Water and Climate Change 11, no. 4 (2019): 966–79. http://dx.doi.org/10.2166/wcc.2019.055.

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Abstract Non-stationary flood frequency analysis (NFFA) plays an important role in addressing the issue of the stationary assumption (independent and identically distributed flood series) that is no longer valid in infrastructure-designed methods. This confirms the necessity of developing new statistical models in order to identify the change of probability functions over time and obtain a consistent flood estimation method in NFFA. The method of Trimmed L-moments (TL-moments) with time covariate is confronted with the L-moment method for the stationary and non-stationary generalized extreme v

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14

Kryvyi, O. F., M. V. Miyusov, and M. O. Kryvyi. "MATHEMATICAL MODELING OF THE OPERATION OF SHIP'S PROPELLERS WITH DIFFERENT MANEUVERING MODES." Shipping & Navigation 32, no. 2 (2021): 71–87. http://dx.doi.org/10.31653/2306-5761.32.2021.71-87.

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In the study of ship maneuvers, in the development of ship's autopilots and simulators, the availability of adequate mathematical models of the ship’s propulsion complex, which would describe with high accuracy the dynamics of the ship for the widest ranges of phase coordinates, plays a decisive role. Mathematical models of ship dynamics consist of mathematical models of inertial and non-inertial forces and moments on the ship's hull. The latter include hydrodynamic and aerodynamic forces and moments on the ship's hull, forces and moments caused by the operation of propellers, rigging, ship ru

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15

Kytölä, Ulla, and Anssi Laaksonen. "Prediction of Restraint Moments in Precast, Prestressed Structures Made Continuous." Nordic Concrete Research 59, no. 1 (2018): 73–93. http://dx.doi.org/10.2478/ncr-2018-0016.

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Abstract This paper studies restraint moments developing in simple-span precast, prestressed beams made continuous. Methods of evaluating restraint moments produced by creep and differential shrinkage are presented. Shrinkage and creep properties of composite structures, beam and deck parts were tested and compared to values defined according to Eurocode models. Finally, the restraint moments were calculated with both material models for the two-span parking deck structure. The study confirmed the findings of previous studies: that the methods that are used overestimate the negative restraint

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16

Dedík, L., and M. Ďurišová. "General Moments in Linear Pharmacokinetic Models." Clinical Research and Regulatory Affairs 13, no. 3-4 (1996): 199–210. http://dx.doi.org/10.3109/10601339609035952.

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17

Bentarzi, M., and M. Merzougui. "Moments of Mixture Periodic Autoregressive Models." Communications in Statistics - Theory and Methods 40, no. 22 (2011): 3937–47. http://dx.doi.org/10.1080/03610926.2010.503017.

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18

Wu, Ping, Yun Fang, and Li-Xing Zhu. "Estimating Moments in Linear Mixed Models." Communications in Statistics - Theory and Methods 37, no. 16 (2008): 2582–94. http://dx.doi.org/10.1080/03610920801947644.

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19

Chan, April S., Helen H. N. Yan, and Suet Yi Leung. "Breakthrough Moments: Organoid Models of Cancer." Cell Stem Cell 24, no. 6 (2019): 839–40. http://dx.doi.org/10.1016/j.stem.2019.05.006.

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20

Bosdogianni, P., M. Petrou, and J. Kittler. "Mixture models with higher order moments." IEEE Transactions on Geoscience and Remote Sensing 35, no. 2 (1997): 341–53. http://dx.doi.org/10.1109/36.563273.

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21

Huang, Zhiyue, and Paul Marriott. "Parameterizing mixture models with generalized moments." Annals of the Institute of Statistical Mathematics 68, no. 2 (2014): 269–97. http://dx.doi.org/10.1007/s10463-014-0490-9.

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22

Kurdyaeva, Tamara, and Andreas Milias-Argeitis. "Uncertainty propagation for deterministic models of biochemical networks using moment equations and the extended Kalman filter." Journal of The Royal Society Interface 18, no. 181 (2021): 20210331. http://dx.doi.org/10.1098/rsif.2021.0331.

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Differential equation models of biochemical networks are frequently associated with a large degree of uncertainty in parameters and/or initial conditions. However, estimating the impact of this uncertainty on model predictions via Monte Carlo simulation is computationally demanding. A more efficient approach could be to track a system of low-order statistical moments of the state. Unfortunately, when the underlying model is nonlinear, the system of moment equations is infinite-dimensional and cannot be solved without a moment closure approximation which may introduce bias in the moment dynamic

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23

Morrison, Hugh, Matthew R. Kumjian, Charlotte P. Martinkus, Olivier P. Prat, and Marcus van Lier-Walqui. "A General N-Moment Normalization Method for Deriving Raindrop Size Distribution Scaling Relationships." Journal of Applied Meteorology and Climatology 58, no. 2 (2019): 247–67. http://dx.doi.org/10.1175/jamc-d-18-0060.1.

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AbstractA general drop size distribution (DSD) normalization method is formulated in terms of generalized power series relating any DSD moment to any number and combination of reference moments. This provides a consistent framework for comparing the variability of normalized DSD moments using different sets of reference moments, with no explicit assumptions about the DSD functional form (e.g., gamma). It also provides a method to derive any unknown moment plus an estimate of its uncertainty from one or more known moments, which is relevant to remote sensing retrievals and bulk microphysics sch

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24

Kuba, Markus, and Alois Panholzer. "Limiting Distributions for a Class Of Diminishing Urn Models." Advances in Applied Probability 44, no. 1 (2012): 87–116. http://dx.doi.org/10.1239/aap/1331216646.

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In this work we analyze a class of 2 × 2 Pólya-Eggenberger urn models with ball replacement matrix and c = pa with . We determine limiting distributions by obtaining a precise recursive description of the moments of the considered random variables, which allows us to deduce asymptotic expansions of the moments. In particular, we obtain limiting distributions for the pills problem a = c = d = 1, originally proposed by Knuth and McCarthy. Furthermore, we also obtain limiting distributions for the well-known sampling without replacement urn, a = d = 1 and c = 0, and generalizations of it to arbit

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25

Kuba, Markus, and Alois Panholzer. "Limiting Distributions for a Class Of Diminishing Urn Models." Advances in Applied Probability 44, no. 01 (2012): 87–116. http://dx.doi.org/10.1017/s0001867800005462.

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In this work we analyze a class of 2 × 2 Pólya-Eggenberger urn models with ball replacement matrix and c = pa with . We determine limiting distributions by obtaining a precise recursive description of the moments of the considered random variables, which allows us to deduce asymptotic expansions of the moments. In particular, we obtain limiting distributions for the pills problem a = c = d = 1, originally proposed by Knuth and McCarthy. Furthermore, we also obtain limiting distributions for the well-known sampling without replacement urn, a = d = 1 and c = 0, and generalizations of it to arbit

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26

Nghiem, Linh H., Michael C. Byrd, and Cornelis J. Potgieter. "Estimation in linear errors-in-variables models with unknown error distribution." Biometrika 107, no. 4 (2020): 841–56. http://dx.doi.org/10.1093/biomet/asaa025.

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Summary Parameter estimation in linear errors-in-variables models typically requires that the measurement error distribution be known or estimable from replicate data. A generalized method of moments approach can be used to estimate model parameters in the absence of knowledge of the error distributions, but it requires the existence of a large number of model moments. In this paper, parameter estimation based on the phase function, a normalized version of the characteristic function, is considered. This approach requires the model covariates to have asymmetric distributions, while the error d

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27

Winterstein, S. R., and C. H. Lange. "Load Models for Fatigue Reliability From Limited Data." Journal of Solar Energy Engineering 118, no. 1 (1996): 64–68. http://dx.doi.org/10.1115/1.2847953.

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Probability distributions of wind turbine loads are estimated from limited data. The impact of different models on fatigue damage is shown. Common one-parameter probability models, such as the Rayleigh and exponential, are found to give significantly different estimates of load distributions and damage. Greatest differences occur in materials with relatively high values of the S–N exponent b, such as composites. In such cases more accurate damage estimates are found by matching at least two moments of the load data (Weibull model), or still higher moments as well. For this purpose, a new, four

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Wang, Zhi Yun, and Shou Ju Li. "Analytical Computational Models for Relationship between Ultimate Bending Moment of Concrete Segments and Axial Force." Key Engineering Materials 853 (July 2020): 177–81. http://dx.doi.org/10.4028/www.scientific.net/kem.853.177.

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Concrete segments are widely used to support soil and water loadings in shield-excavated tunnels. Concrete segments burden simultaneously to the loadings of bending moments and axial forces. Based on plane deformation assumption of material mechanics, in which plane section before bending remains plane after bending, ultimate bending moment model is proposed to compute ultimate bearing capacity of concrete segments. Ultimate bending moments of concrete segments computed by analytical models agree well with numerical simulation results by FEM. The accuracy of proposed analytical computational m

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Lynth, Thomas B., Timothy A. Max, Harold E. Burkhart, and Jiping Liu. "Prediction Equations for Centers of Gravity and Moments of Inertia of Loblolly Pine Stems." Forest Science 39, no. 2 (1993): 260–74. http://dx.doi.org/10.1093/forestscience/39.2.260.

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Abstract Adequate design of tree harvesting equipment requires reliable estimates of centers of gravity and moments of inertia for full trees and tree-length stems. Several prediction models were developed for both centers of gravity and moments of inertia based on the theory of geometric solids. These models were fitted to center of gravity and moment of inertia estimates that were derived from stem dimension and weight measurements on loblolly pine (Pinus taeda L.) trees. The models were compared, and the best prediction equations for center of gravity and moment of inertia of tree-length st

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Anghelache Nastase, Iulia-Nela, Simona Moldovanu, and Luminita Moraru. "Image Moment-Based Features for Mass Detection in Breast US Images via Machine Learning and Neural Network Classification Models." Inventions 7, no. 2 (2022): 42. http://dx.doi.org/10.3390/inventions7020042.

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Differentiating between malignant and benign masses using machine learning in the recognition of breast ultrasound (BUS) images is a technique with good accuracy and precision, which helps doctors make a correct diagnosis. The method proposed in this paper integrates Hu’s moments in the analysis of the breast tumor. The extracted features feed a k-nearest neighbor (k-NN) classifier and a radial basis function neural network (RBFNN) to classify breast tumors into benign and malignant. The raw images and the tumor masks provided as ground-truth images belong to the public digital BUS images data

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Heine, Richard, Kurt Manal, and Thomas S. Buchanan. "Using Hill-Type Muscle Models and EMG Data in a Forward Dynamic Analysis of Joint Moment." Journal of Mechanics in Medicine and Biology 03, no. 02 (2003): 169–86. http://dx.doi.org/10.1142/s0219519403000727.

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There has been considerable interest in estimating muscle forces and joint moments from EMG signals, but most approaches have not been very successful. This is largely because robust models of muscle activation dynamics, Hill-type muscle contraction dynamics, and musculoskeletal geometry are generally not included. Here we present a model which includes these sub-models and we determine which model parameters are most important. The models abilities to predict joint moments about the human elbow during time-varying isometric tasks were examined. Inputs to the models were EMGs from eight muscle

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Issermann, Maikel, and Fi-John Chang. "Uncertainty Analysis of Spatiotemporal Models with Point Estimate Methods (PEMs)—The Case of the ANUGA Hydrodynamic Model." Water 12, no. 1 (2020): 229. http://dx.doi.org/10.3390/w12010229.

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Practitioners often neglect the uncertainty inherent to models and their inputs. Point Estimate Methods (PEMs) offer an alternative to the common, but computationally demanding, method for assessing model uncertainty, Monte Carlo (MC) simulation. PEMs rerun the model with representative values of the probability distribution of the uncertain variable. The results can estimate the statistical moments of the output distribution. Hong’s method is the specific PEM implemented here for a case study that simulates water runoff using the ANUGA model for an area in Glasgow, UK. Elevation is the source

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Dunne, Adrian. "Statistical Moments in Pharmacokinetics: Models and Assumptions." Journal of Pharmacy and Pharmacology 45, no. 10 (1993): 871–75. http://dx.doi.org/10.1111/j.2042-7158.1993.tb05611.x.

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Appelquist, Thomas, Maurizio Piai, and Robert Shrock. "Lepton dipole moments in extended technicolor models." Physics Letters B 593, no. 1-4 (2004): 175–80. http://dx.doi.org/10.1016/j.physletb.2004.04.062.

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Juliá-Dı́az, B., and D. O. Riska. "Baryon magnetic moments in relativistic quark models." Nuclear Physics A 739, no. 1-2 (2004): 69–88. http://dx.doi.org/10.1016/j.nuclphysa.2004.03.078.

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Jakubowski, Jacek, and Jerzy Zabczyk. "Exponential moments for HJM models with jumps." Finance and Stochastics 11, no. 3 (2007): 429–45. http://dx.doi.org/10.1007/s00780-007-0040-x.

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Li, Zaixing, Fei Chen, and Lixing Zhu. "Estimating moments in ANOVA-type mixed models." Metrika 80, no. 6-8 (2017): 697–715. http://dx.doi.org/10.1007/s00184-017-0623-2.

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Couture, G., J. N. Ng, J. L. Hewett, and T. G. Rizzo. "Anomalous moments ofWbosons in broken-supersymmetric models." Physical Review D 38, no. 3 (1988): 860–64. http://dx.doi.org/10.1103/physrevd.38.860.

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Castella, F., G. Dujardin, and B. Sericola. "Moments’ Analysis in Homogeneous Markov Reward Models." Methodology and Computing in Applied Probability 11, no. 4 (2008): 583–601. http://dx.doi.org/10.1007/s11009-008-9075-5.

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Agbonaye, Augustine Iyekeoretin, Ebierin Akpoebidimiyen Otuaro, and Osadolor Christopher Izinyon. "COMPARISON OF L-MOMENT AND METHOD OF MOMENTS AS PARAMETER ESTIMATORS FOR IDENTIFICATION AND CHOICE OF THE MOST APPROPRIATE RAINFALL DISTRIBUTION MODELS FOR DESIGN OF HYDRAULIC STRUCTURES." Journal of Civil Engineering, Science and Technology 13, no. 1 (2022): 33–48. http://dx.doi.org/10.33736/jcest.4207.2022.

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In rainfall frequency analysis, the choice of a suitable probability distribution and parameter estimation method is critical in forecasting design rainfall values for varying return periods at every location. Previously, some researchers in Nigeria used the method of moments (MoM) while others used the L-moment method (LMM) as parameter estimators. However, a more accurate result is obtainable if both estimators are used and their results are compared and ranked to obtain the most appropriate distribution models for each location This study compared the performance of two forms of parameter e

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Bebu, Ionut, and Thomas Mathew. "Confidence intervals for limited moments and truncated moments in normal and lognormal models." Statistics & Probability Letters 79, no. 3 (2009): 375–80. http://dx.doi.org/10.1016/j.spl.2008.09.006.

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Yee, Albert G., and C. Daniel Mote. "Forces and Moments at the Knee and Boot Top: Models for an Alpine Skiing Population." Journal of Applied Biomechanics 13, no. 3 (1997): 373–84. http://dx.doi.org/10.1123/jab.13.3.373.

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The purpose of this study was to identify regression models to predict moments at the boot top and knee from the force components at the bindings for a sample of skiers. Six subjects skied a slalom course, first with their boots set to the least stiff setting and then with their boots set to the most stiff setting. Six load component dynamometers measured force and moment components at the toe and heel bindings. An electrogoniometer measured ankle flexion. Regression models were developed for the subject sample that predicted quasi-static moment components at the boot top and knee from measure

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TAMRAZYAN, A. G., and Y. A. K. SAYED. "EXPERIMENTAL STUDY OF THE COEFFICIENT OF MOMENT REDISTRIBUTION IN STATICALLY INDETERMINATE RC BEAMS." Building and reconstruction 109, no. 5 (2023): 24–35. http://dx.doi.org/10.33979/2073-7416-2023-109-5-24-35.

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This article investigates the coefficient of moments redistribution in statically indeterminate RC beams through an experimental and analytical approach. Two-span statically indeterminate RC beams were tested under bending moment. A discussion of the results of the mode of failure, load-deformation, load-strain, and the coefficient of the moments redistribution were conducted. Moreover, the experimental results were compared to the analytical predictions of the related existing models, including the ACI 318-19 and CSA A23.3-19 codes, and others. The results show that the coefficient of moment

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Nail-Ulloa, Ivan, Sean Gallagher, Rong Huangfu, Dania Bani-Hani, and Nathan Pool. "Validation of a Wireless Sensor System for the Estimation of Cumulative Lumbar Loads in Occupational Settings." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, no. 1 (2021): 489–94. http://dx.doi.org/10.1177/1071181321651078.

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This study aimed to evaluate the accuracy of 3D L5/S1 moment estimates from a wearable inertial motioncapture system during manual lifting tasks. Reference L5/S1 moments were calculated using inversedynamics bottom-up and top-down laboratory models, based on the data from a measurement systemcomprising optical motion capture and force plates. Nine groups of four subjects performed tasks consistingof lifting and lowering 10 lbs. load with three different heights and asymmetry angles. As a measure ofsystem performance, the root means square errors and absolute peak errors between models werecomp

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Yu, Kaizhi, and Hong Zou. "The Combined Poisson INMA(q) Models for Time Series of Counts." Journal of Applied Mathematics 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/457842.

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A new stationaryqth-order integer-valued moving average process with Poisson innovation is introduced based on decision random vector. Some statistical properties of the process are established. Estimators of the parameters of the process are obtained using the method of moments. Some numerical results of the estimators are presented to assess the performance of moment estimators.

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Winterstein, Steven R., and Tina Kashef. "Moment-Based Load and Response Models With Wind Engineering Applications." Journal of Solar Energy Engineering 122, no. 3 (2000): 122–28. http://dx.doi.org/10.1115/1.1288028.

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A general method is shown here to model wind loads and responses for reliability applications. This method characterizes the short-term loads and responses by a few summary statistics: specifically, by a limited number of statistical moments. A suite of moment-based models are derived and applied here, illustrating how this statistical moment information can best be utilized. Two examples are shown: the fatigue analysis of a wind turbine component, and the vibration response of a fixed structure to nonlinear wind drag loads. [S0199-6231(00)00702-4]

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47

Armstrong, Timothy B., and Michal Kolesár. "Sensitivity analysis using approximate moment condition models." Quantitative Economics 12, no. 1 (2021): 77–108. http://dx.doi.org/10.3982/qe1609.

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Abstract (sommario):

We consider inference in models defined by approximate moment conditions. We show that near‐optimal confidence intervals (CIs) can be formed by taking a generalized method of moments (GMM) estimator, and adding and subtracting the standard error times a critical value that takes into account the potential bias from misspecification of the moment conditions. In order to optimize performance under potential misspecification, the weighting matrix for this GMM estimator takes into account this potential bias and, therefore, differs from the one that is optimal under correct specification. To forma

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48

Armstrong, Timothy B., and Michal Kolesár. "Sensitivity analysis using approximate moment condition models." Quantitative Economics 12, no. 1 (2021): 77–108. http://dx.doi.org/10.3982/qe1609.

Testo completo

Abstract (sommario):

We consider inference in models defined by approximate moment conditions. We show that near‐optimal confidence intervals (CIs) can be formed by taking a generalized method of moments (GMM) estimator, and adding and subtracting the standard error times a critical value that takes into account the potential bias from misspecification of the moment conditions. In order to optimize performance under potential misspecification, the weighting matrix for this GMM estimator takes into account this potential bias and, therefore, differs from the one that is optimal under correct specification. To forma

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49

Pedersen, Rasmus Søndergaard. "TARGETING ESTIMATION OF CCC-GARCH MODELS WITH INFINITE FOURTH MOMENTS." Econometric Theory 32, no. 2 (2015): 498–531. http://dx.doi.org/10.1017/s0266466615000316.

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Abstract (sommario):

As an alternative to quasi-maximum likelihood, targeting estimation is a much applied estimation method for univariate and multivariate GARCH models. In terms of variance targeting estimation, recent research has pointed out that at least finite fourth moments of the data generating process is required, if one wants to perform inference in GARCH models by relying on asymptotic normality of the estimator. Such moment conditions may not be satisfied in practice for financial returns, highlighting a potential drawback of variance targeting estimation. In this paper, we consider the large-sample p

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50

Albert, Wayne J., Joan M. Stevenson, Geneviève A. Dumas, and Roger W. Wheeler. "Effects of shoulder translation on lumbar moment for two dimensional modeling strategies during lifting." Occupational Ergonomics 1, no. 3 (1998): 173–87. http://dx.doi.org/10.3233/oer-1998-1302.

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Abstract (sommario):

The objectives of this study were to: 1) develop a dynamic 2D link segment model for lifting using the constraints of four sensors from an electromagnetic motion analysis system; 2) evaluate the magnitude of shoulder movement in the sagittal plane during lifting; and 3) investigate the effect of shoulder translation on trunk acceleration and lumbar moments calculated by the developed model and comparing it with two separate 2D dynamic link segment models. Six women and six men lifted loads of 2 kg, 7 kg, 12 kg and 2 kg, 12 kg, 22 kg respectively, under stoop, squat and freestyle conditions. Tr

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