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On simulation of first-order auto-regressive processes with near Laplace marginals
2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009The focus of this paper is the modeling of a class of stationary non-Gaussian auto-regressive processes that often find applications in statistical signal processing. We propose a general simulation procedure for constructing a time series model with a near-Laplace marginal distributions.
Mirek Pawlak, Pradeepa Yahampath
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Gaussian Process Auto Regression for vehicle center coordinates Trajectory Prediction
TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON), 2019With the increase in autonomous car technology, and advance driver assistance systems (ADAS), the demand for vehicle trajectory prediction is increasing. These systems mostly use many sensors such as lidar, radar, stereo cameras which are big and expensive to detect the location of the ego vehicles with respect to other vehicles.
Qun Lim, Kritika Johari, U-Xuan Tan
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A weighted auto regressive LSTM based approach for chemical processes modeling
Neurocomputing, 2019Abstract Data-driven methods have been regarded as effective methods for modeling in chemical processes. However, with the increasing complexity of chemical processes in spatial domain and time domain, how to extract meaningful features and build corresponding models are keys for accurate modeling tasks. To retain temporal features of original inputs,
Xu Zhang +3 more
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Dynamic synthetic control method for evaluating treatment effects in auto-regressive processes
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2023Abstract Motivated by evaluating the effects of air pollution alerts on air quality, we propose the dynamic synthetic control method for micro-level data with time-varying confounders and spatial dependence under an auto-regressive model setting.
Xiangyu Zheng, Song Xi Chen
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Dual auto-regressive modelling approach to Gaussian process identification
IEEE International Conference on Multimedia and Expo, 2001. ICME 2001., 2001By modelling sources as a multivariate auto-regressive (AR) process, we have recently presented a dual AR modelling approach to identify temporal sources in independent component analysis (ICA) (Cheung et al. 2000, Cheung and Xu 1999 & 2001). However, our proposed existing algorithms for this approach are only suitable for the case that the residual ...
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GLM based auto-regressive process to model Covid-19 pandemic in Turkey
Statistical Communications in Infectious Diseases, 2021Abstract Objectives: Our objective is to propose a robust approach to model daily new cases and daily new deaths due to covid-19 infection in Turkey. Methods: We consider the generalized linear model (GLM) approach ...
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Asymmetric heavy-tailed vector auto-regressive processes with application to financial data
Journal of Statistical Computation and Simulation, 2019Vector Auto-regressive (VAR) models are commonly used for modelling multivariate time series and the typical distributional form is to assume a multivariate normal. However, the assumption of Gaussian white noise in multivariate time series is often not reasonable in applications where there are extreme and/or skewed observations.
Mohsen Maleki +3 more
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Time neighborhood preserving auto-regressive model for industrial process monitoring
Engineering Research ExpressAbstract The mandatory requirement of ensuring plant safety as well as sustainable operation keeps motivating novel approaches for trustfully detecting anomalies or faults during production. Recently, a unified modeling framework which extracts latent variables (LVs) with explicit interpretation to time-serial variation, is becoming ...
Huatong Dai, Chudong Tong, Lijia Luo
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Exploring the processes of firm growth: evidence from a vector auto-regression
Industrial and Corporate Change, 2010This article offers many new insights into the processes of firm growth by applying a vector autoregression model to longitudinal panel data on French manufacturing firms. We observe the coevolution of key variables such as growth of employment, sales, gross operating surplus, and labor productivity growth.
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Visibility graph analysis for re-sampled time series from auto-regressive stochastic processes
Communications in Nonlinear Science and Numerical Simulation, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rong Zhang +4 more
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