Results 11 to 20 of about 1,397,164 (333)
Bayesian Trace Statistics for the Reduced Rank Regression Model [PDF]
, 2017 Estimation of the reduced rank regression model requires restrictions be imposed upon the model. Two forms of restrictions are commonly used. Earlier Bayesian work relied on the triangular method of identification which imposes an a priori ordering on the variables in the system, however, incorrect ordering of the variables can result in model ...
Rodney W. Strachan, Brett Inder
openalex +2 more sources
Reduced-Rank Covariance Estimation in Vector Autoregressive Modeling [PDF]
, 2014 We consider reduced-rank modeling of the white noise covariance matrix in a large dimensional vector autoregressive (VAR) model. We first propose the reduced-rank covariance estimator under the setting where independent observations are available. We derive the reduced-rank estimator based on a latent variable model for the vector observation and give ...
Richard A. Davis +2 more
openalex +3 more sources
The VGAM Package for Categorical Data Analysis [PDF]
Journal of Statistical Software, 2010 Classical categorical regression models such as the multinomial logit and proportional odds models are shown to be readily handled by the vector generalized linear and additive model (VGLM/VGAM) framework. Additionally, there are natural extensions, such
Thomas W. Yee
doaj +1 more source
A RESONANCE CALCULATION METHOD USING ENERGY EXPANSION BASED ON A REDUCED ORDER MODEL: USE OF ULTRA-FINE GROUP SPECTRUM CALCULATION AND APPLICATION TO HETEROGENEOUS GEOMETRY [PDF]
EPJ Web of Conferences, 2021 A Resonance calculation using energy Spectral Expansion (RSE) method has been recently proposed in order to efficiently treat complicated heterogeneous geometry and resonance interference effect.
Kondo Ryoichi +7 more
doaj +1 more source
Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach [PDF]
30 pages, 6 ...
Alain Hecq, Ivan Ricardo, Ines Wilms
openalex +4 more sources
Reduced-Rank Envelope Vector Autoregressive Model
Journal of Business & Economic Statistics, 2023 The standard vector autoregressive (VAR) models suffer from overparameterization which is a serious issue for high-dimensional time series data as it restricts the number of variables and lags that can be incorporated into the model. Several statistical methods, such as the reduced-rank model for multivariate (multiple) time series (Velu, Reinsel, and ...
S. Yaser Samadi +1 more
openaire +2 more sources
Resonance Calculation Method Based on Energy Spectrum Using Reduced Order Model
Yuanzineng kexue jishu, 2023 Resonance calculation is one of the most important and difficult parts of core analysis and can dominate the accuracy of the core analysis. There are three methods for resonance computation: ultra-fine group (UFG) method, equivalence method, and subgroup
YU Jialei;ZHANG Qian;ZHANG Jinchao;ZHAO Qiang
doaj +1 more source
Efficient Conformer Model Based on Factorized Gated Attention Unit [PDF]
Jisuanji gongcheng, 2023 To reduce the number of model parameters and accelerate the training and recognition speed while ensuring the accuracy of the Conformer end-to-end speech recognition model，an efficient Conformer model based on Factorized Gated Attention Unit（FGAU） and ...
LI Yiting, QU Dan, YANG Xukui, ZHANG Hao, SHEN Xiaolong
doaj +1 more source
Econometrics, 2022 For more than half a century, Manfred Deistler has been contributing to the construction of the rigorous theoretical foundations of the statistical analysis of time series and more general stochastic processes.
Marc Hallin
doaj +1 more source
Complex Impacts of Traffic Citations on Road Safety
Future Transportation, 2022 Wyoming has one of the highest fatality rates and lowest enforcement rates in the U.S. Thus, this study was conducted to see if there is any link between various citation types on the equivalent property damage only (EPDO) crashes, while taking into ...
Mahdi Rezapour, Khaled Ksaiabti
doaj +1 more source