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Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019
This study models weekly dengue case counts with two climatological variables: temperature and precipitation. Since conventional zero‐inflated integer‐valued generalized auto‐regressive conditional heteroscedastic (GARCH) models and Poisson regression ...
Cathy W. S. Chen +2 more
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This study models weekly dengue case counts with two climatological variables: temperature and precipitation. Since conventional zero‐inflated integer‐valued generalized auto‐regressive conditional heteroscedastic (GARCH) models and Poisson regression ...
Cathy W. S. Chen +2 more
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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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IEEE Transactions on Neural Networks, 2011
This paper analyzes the expected time evolution of an auto-regressive (AR) process using self-organized maps (SOM). It investigates how a SOM captures the time information given by the AR input process and how the transitions from one neuron to another one can be understood under a probabilistic perspective. In particular, regions of the map into which
Brighenti, Chiara +1 more
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This paper analyzes the expected time evolution of an auto-regressive (AR) process using self-organized maps (SOM). It investigates how a SOM captures the time information given by the AR input process and how the transitions from one neuron to another one can be understood under a probabilistic perspective. In particular, regions of the map into which
Brighenti, Chiara +1 more
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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.
Zhang, Rong +4 more
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A Novel Auto-regressive Dynamic Slow Feature Analysis Method for Dynamic chemical Process Monitoring
Chemical Engineering and Science, 2021Yuemei Xu, Mingxing Jia, Zhizhong Mao
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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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About First Order Geometric Auto Regressive Processes for Boundary Layer Wind Speed Simulation
2009Under certain conditions the first order geometric auto regressive process has statistical properties similar to atmospheric boundary layer wind speed. In this contribution, we investigate this similarity and analyse the extent to which this stochastic process is a suitable model for wind speed simulation.
Laubrich, T., Kantz, H.
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Estimation of possibly non-stationary first-order auto-regressive processes
2016This paper inspects a grid search algorithm to estimate the AR(1) process, based on the joint estimation of the canonical AR(1) equation along with its reverse form. The method relies on the GLS principle, accounting for the covariance error structure of the special estimable system.
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Vehicle speed prediction using a cooperative method of fuzzy Markov model and auto-regressive model
2017 IEEE Intelligent Vehicles Symposium (IV), 2017Junbo Jing +5 more
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