{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting
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Updated
Jun 28, 2024 - R
{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting
Bayesian Estimation of Structural Vector Autoregressive Models
Functions for Bayesian inference of vector autoregressive and vector error correction models
State-Dependent Empirical Analysis: tools for state-dependent forecasts, impulse response functions, historical decomposition, and forecast error variance decomposition.
Regularized estimation of high-dimensional FAVAR models
Implementation of the FNETS methodology proposed in Barigozzi, Cho and Owens (2024) for network estimation and forecasting of high-dimensional time series
Code to reproduce paper Adrian, Duarte and Iyer (2023), “The Market Price of Risk and Macro-Financial Dynamics”
An R package to model BVHAR
Personal repository for hobby and work projects
Repository for: Chiovaro, M., Windsor, L. C., & Paxton, A. (2021). Vector Autoregression, Cross-Correlation, and Cross-Recurrence Quantification Analysis: A Case Study in Social Cohesion and Collective Action. In CogSci.
Analysis scripts and randomly generated data for Suicide and Life-Threatening Behavior paper: 'Identifying person-specific coping responses to suicidal urges: A case series analysis and illustration of the idiographic method'
Codes for BVHAR Research
Research project: Could Interest Rate Hikes Burst The Housing Bubble?
Convenient functions to generate multivariate time series in the vector autoregressive framework.
VAR and Local Projections
An R package for Bayesian Estimation of Structural Vector Autoregressive Models
Research project: The Impact of Uncertainty on Monetary Transmission - Evidence from the US
data segmentation and forecasting for VAR-driven factor models
Estimates latent class vector-autoregressive models via EM algorithm on time-series data for model-based clustering and classification. Includes model selection criteria for selecting the number of lags and clusters.
Estimação de modelos VAR(3) e VAR(10) para 91 países no período de 1960 a 2019, a fim de testar a causalidade de Granger entre as variáveis de Poupança Interna Bruta e crescimento do Produto Interno Bruto per capita.
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