標(biāo)題: Titlebook: Bayesian Statistics from Methods to Models and Applications; Research from BAYSM Sylvia Frühwirth-Schnatter,Angela Bitto,Alexandra Confer [打印本頁] 作者: MOTE 時間: 2025-3-21 16:47
書目名稱Bayesian Statistics from Methods to Models and Applications影響因子(影響力)
書目名稱Bayesian Statistics from Methods to Models and Applications影響因子(影響力)學(xué)科排名
書目名稱Bayesian Statistics from Methods to Models and Applications網(wǎng)絡(luò)公開度
書目名稱Bayesian Statistics from Methods to Models and Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Bayesian Statistics from Methods to Models and Applications被引頻次
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書目名稱Bayesian Statistics from Methods to Models and Applications讀者反饋學(xué)科排名
作者: narcotic 時間: 2025-3-21 21:00 作者: 斗爭 時間: 2025-3-22 01:44 作者: GRIPE 時間: 2025-3-22 06:14 作者: FUME 時間: 2025-3-22 09:13 作者: 兇殘 時間: 2025-3-22 14:47 作者: 引起 時間: 2025-3-22 17:38 作者: 的染料 時間: 2025-3-23 00:46
A Subordinated Stochastic Process Modelare irregularly spaced in time or different curves that are observed at different moments of time. With the use of simulations and applications, we examine two approaches to Bayesian inference for our model: the first based on a Gibbs sampler and the second based on approximate Bayesian computation (ABC).作者: 深陷 時間: 2025-3-23 03:34 作者: Mri485 時間: 2025-3-23 07:36 作者: 影響深遠(yuǎn) 時間: 2025-3-23 13:44
Haochen Cui,Yuntian Duan,Baojin Dinge employ computer simulations for producing mock samples, and account for variation between samples for modelling the likelihood function. We also consider the effects on the likelihood, and consequential ability to compare competing hypotheses, if only simplistic computer simulations are available.作者: 洞穴 時間: 2025-3-23 16:05 作者: crockery 時間: 2025-3-23 21:36
General Conclusion and Outlook,onsidering heating and cooling cycles given to a specimen made up of polymethylmethacrylate (PMMA) in forced convection. Results show good estimates in accordance with the PMMA conductivity range, and computational times confirm the possibility of a real-time estimation.作者: 僵硬 時間: 2025-3-23 22:35
A New Strategy for Testing Cosmology with Simulationse employ computer simulations for producing mock samples, and account for variation between samples for modelling the likelihood function. We also consider the effects on the likelihood, and consequential ability to compare competing hypotheses, if only simplistic computer simulations are available.作者: ingestion 時間: 2025-3-24 05:08 作者: cortisol 時間: 2025-3-24 08:16
Bayesian Filtering for Thermal Conductivity Estimation Given Temperature Observationsonsidering heating and cooling cycles given to a specimen made up of polymethylmethacrylate (PMMA) in forced convection. Results show good estimates in accordance with the PMMA conductivity range, and computational times confirm the possibility of a real-time estimation.作者: Instantaneous 時間: 2025-3-24 12:29 作者: Psa617 時間: 2025-3-24 16:35 作者: dictator 時間: 2025-3-24 20:25 作者: WITH 時間: 2025-3-25 00:07 作者: Relinquish 時間: 2025-3-25 04:17 作者: 越自我 時間: 2025-3-25 10:45
A Mixture Model for Filtering Firms’ Profit Rates. We find the Laplace specification to have a superior fit based on the Bayes factor and the profit rate sample to be time stationary Laplace distributed, corroborating earlier estimates of cross-section distributions. Our model retains 97?%, as opposed to as little as 20?%, of the raw data in a previous application.作者: MIR 時間: 2025-3-25 12:10 作者: 造反,叛亂 時間: 2025-3-25 19:54 作者: NOVA 時間: 2025-3-25 23:54 作者: 紋章 時間: 2025-3-26 02:56 作者: orthodox 時間: 2025-3-26 05:45
Bayesian Statistics from Methods to Models and ApplicationsResearch from BAYSM 作者: 文件夾 時間: 2025-3-26 11:48 作者: 顯赫的人 時間: 2025-3-26 15:53
Evaluation of Dummy Neck Performanceate the derived posterior distribution via a Metropolis–Hastings algorithm and the behavior of the simulated chains is investigated to reach evidence in favor of the properness of the posterior distribution.作者: 收集 時間: 2025-3-26 18:54 作者: meretricious 時間: 2025-3-26 22:45
2194-1009 thods, as well as a lively poster session with 30 contributions. Selected contributions have been drawn from the conference for this book. All contributions in this volume are peer-reviewed and share original r978-3-319-36234-2978-3-319-16238-6Series ISSN 2194-1009 Series E-ISSN 2194-1017 作者: Demonstrate 時間: 2025-3-27 02:06 作者: 口味 時間: 2025-3-27 09:12
A New Finite Approximation for the NGG Mixture Model: An Application to Density Estimationilt from the representation of the NGG process as a discrete measure, where the weights are obtained by normalization of points of a Poisson process larger than a threshold .. Consequently, the new process has an as surely finite number of location points. This process is then considered as the mixi作者: 抑制 時間: 2025-3-27 11:31 作者: 雜色 時間: 2025-3-27 15:19 作者: 苦惱 時間: 2025-3-27 18:42
A Subordinated Stochastic Process Modelction via subordination. This model is useful in many applications such as growth curves (children’s height, fish length, diameter of trees, etc.) and degradation processes (crack size, wheel degradation, laser light, etc.). One advantage of our approach is the ability to easily deal with data that 作者: 天文臺 時間: 2025-3-28 00:48
Bayesian Variable Selection for Generalized Linear Models Using the Power-Conditional-Expected-Poste and expected-posterior prior, relying on the concept of random imaginary data, and provides a consistent variable selection method which leads to parsimonious selection. In this paper, the PCEP methodology is extended to generalized linear models (GLMs). We define the PCEP prior in the GLM setting,作者: 安慰 時間: 2025-3-28 03:04
Application of Interweaving in DLMs to an Exchange and Specialization ExperimentWong, J. Am. Stat. Assoc. 82(398):528–540, 1987) is a commonly used approach, e.g. (Carter and Kohn, Biometrika 81(3):541–553, 1994) and (Frühwirth-Schnatter, J. Time Ser. Anal. 15(2):183–202, 1994) in dynamic linear models. Using two data augmentations, Yu and Meng (J. Comput. Graph. Stat. 20(3): 5作者: 易發(fā)怒 時間: 2025-3-28 09:59 作者: 鳥籠 時間: 2025-3-28 11:21
Identifying the Infectious Period Distribution for Stochastic Epidemic Models Using the Posterior Prmic model. This method seeks to determine whether or not one can identify the infectious period distribution based only on a set of partially observed data using a posterior predictive distribution approach. Our criterion for assessing the model’s goodness of fit is based on the notion of Bayesian r作者: CLAN 時間: 2025-3-28 14:48
A New Strategy for Testing Cosmology with Simulationss, known as .CDM. However, standard approaches are unable to quantify the preference for one hypothesis over another. We advocate using a ‘weighted’ variant of approximate Bayesian computation (ABC), whereby the parameters of the strong lensing-mass scaling relation, . and ., are treated as the summ作者: notion 時間: 2025-3-28 20:51
Formal and Heuristic Model Averaging Methods for Predicting the US Unemployment Rateween linear and nonlinear models and averages of these models. To combine predictive densities, we use two complementary methods: Bayesian model averaging and optimal pooling. We select the individual models combined by these methods with the evolution of Bayes factors over time. Model estimation is作者: Toxoid-Vaccines 時間: 2025-3-28 23:00 作者: 宴會 時間: 2025-3-29 05:57
Bayesian Filtering for Thermal Conductivity Estimation Given Temperature Observationscount the uncertainty in the estimation procedure. In this paper, we propose a particle filtering approach coupled with a simple experimental layout for the real-time estimation of the thermal conductivity in homogeneous materials. Indeed, based on the heat equation, we define a state-space model fo作者: 地牢 時間: 2025-3-29 10:46 作者: 合并 時間: 2025-3-29 11:41
https://doi.org/10.1007/978-3-319-16238-6Applied bayesian statistics; Bayesian estimation; Bayesian statistics; Bayesian statistics applications作者: 不舒服 時間: 2025-3-29 16:21 作者: 為寵愛 時間: 2025-3-29 20:17 作者: 粗糙 時間: 2025-3-30 03:44
Springer Proceedings in Mathematics & Statisticshttp://image.papertrans.cn/b/image/181883.jpg作者: heckle 時間: 2025-3-30 05:05
Identifying the Infectious Period Distribution for Stochastic Epidemic Models Using the Posterior Prmic model. This method seeks to determine whether or not one can identify the infectious period distribution based only on a set of partially observed data using a posterior predictive distribution approach. Our criterion for assessing the model’s goodness of fit is based on the notion of Bayesian residuals.作者: 一個姐姐 時間: 2025-3-30 09:02 作者: 薄膜 時間: 2025-3-30 15:33
Biomechanical Aspects of Head Injuryilt from the representation of the NGG process as a discrete measure, where the weights are obtained by normalization of points of a Poisson process larger than a threshold .. Consequently, the new process has an as surely finite number of location points. This process is then considered as the mixi作者: medium 時間: 2025-3-30 19:18
Impact Response of the Human Thorax means and covariances. The network of cooperating agents is represented by a directed or undirected graph, consisting of vertices taking observations, incorporating them into own statistical knowledge about the inferred parameters and sharing the observations and the posterior knowledge with other 作者: 手榴彈 時間: 2025-3-31 00:19 作者: BINGE 時間: 2025-3-31 03:13
William F. King,Harold J. Mertzction via subordination. This model is useful in many applications such as growth curves (children’s height, fish length, diameter of trees, etc.) and degradation processes (crack size, wheel degradation, laser light, etc.). One advantage of our approach is the ability to easily deal with data that 作者: Inelasticity 時間: 2025-3-31 05:32
Emília Mi?íková Elexová,Jarmila Makovinská and expected-posterior prior, relying on the concept of random imaginary data, and provides a consistent variable selection method which leads to parsimonious selection. In this paper, the PCEP methodology is extended to generalized linear models (GLMs). We define the PCEP prior in the GLM setting,
