To achieve the latter, we propose a Bayesian inference approach to analyze the dynamic interactions among macroeconomics variables in a graphical vector autoregressive model. The method decomposes the structural model into multivariate autoregressive and contemporaneous networks that can be represented in the...
This model leads to a multi-scale representation of the spatio-temporal process. We propose a statistical procedure to estimate the multi-scale structure and the model parameters in the case of the vector autoregressive model with drift. Modeling and estimation tasks are illustrated on simulated and...
This paper proposes a Bayesian, graph‐based approach to identification in vector autoregressive (VAR) models. In our Bayesian graphical VAR (BGVAR) model, the contemporaneous and temporal causal structures of the structural VAR model are represented by two different graphs. We also provide an effic...
This example gives a graphical illustration of low-rank autoregressive tensor completion model. To draw this example, we can follow these steps: preamble codes: define the documentclass as standalone, use both tikz and tikz-3dplot packages. body codes: set \Depth, \Width, and \Height parame...
The package includes functions to estimate, visualize and resample time-varying k-order Mixed Graphical Models (MGMs) and mixed Vector Autoregressive (mVAR) models. Here is a paper describing the package:https://arxiv.org/abs/1510.06871
multivariate vector autoregression process CGI: granger causality index CGCI: conditional Granger causality index ARMA: autoregressive moving average model IPM: integrated pest management References Mysterud A, Yoccoz NG, Langvatn R, Pettorelli N, Stenseth NCh. Hierarchical path analysis of deer...
To achieve the latter, we propose a Bayesian inference approach to analyze the dynamic interactions among macroeconomics variables in a graphical vector autoregressive model. The method decomposes the structural model into multivariate autoregressive and contemporaneous networks that can be represented in the...
Financial networkIn this paper, we propose novel strategies based on Gibbs sampling for the estimation of the coefficients and topology of a graphical network represented by a first-order vector autoregressive model. As the topology and the coefficients are closely related, obtaining their Markov ...
A graphical vector autoregressive modelling approach to the analysis of electronic diary dataMedicine(GeneralBackground In recent years, electronic diaries are increasingly used in medical research and practice to investigate patients' processes and fluctuations in symptoms over time. To model dynamic ...
Currently, the package offers functions to fit a graphical autoregressive -- GAR(1) model through a 3-step procedure. Dependencies Please make sure that the following packages are installed before using the R package SGM. install.packages(c("doParallel", "foreach", "gmp")) Installation The ...