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Achieving Shrinkage in a Time-Varying Parameter Model Framework
v1v2 (latest)

Achieving Shrinkage in a Time-Varying Parameter Model Framework

4 November 2016
A. Bitto
Sylvia Fruhwirth-Schnatter
ArXiv (abs)PDFHTML

Papers citing "Achieving Shrinkage in a Time-Varying Parameter Model Framework"

17 / 17 papers shown
Title
A Structural Text-Based Scaling Model for Analyzing Political Discourse
A Structural Text-Based Scaling Model for Analyzing Political Discourse
Jan Vávra
Bernd Hans-Konrad Prostmaier
Bettina Grün
Paul Hofmarcher
27
1
0
14 Oct 2024
The ARR2 prior: flexible predictive prior definition for Bayesian
  auto-regressions
The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions
David Kohns
Noa Kallioinen
Yann McLatchie
Aki Vehtari
69
1
0
30 May 2024
Bayesian Nonlinear Regression using Sums of Simple Functions
Bayesian Nonlinear Regression using Sums of Simple Functions
Florian Huber
49
1
0
04 Dec 2023
A Bayesian Survival Model for Time-Varying Coefficients and Unobserved
  Heterogeneity
A Bayesian Survival Model for Time-Varying Coefficients and Unobserved Heterogeneity
Peter Knaus
Daniel T. Winkler
G. Jomrich
147
1
0
22 Jun 2022
General Bayesian time-varying parameter VARs for predicting government
  bond yields
General Bayesian time-varying parameter VARs for predicting government bond yields
M. Fischer
Niko Hauzenberger
Florian Huber
Michael Pfarrhofer
26
0
0
26 Feb 2021
Deep Distributional Time Series Models and the Probabilistic Forecasting
  of Intraday Electricity Prices
Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices
Nadja Klein
M. Smith
David J. Nott
BDLAI4TS
54
27
0
05 Oct 2020
Dynamic sparsity on dynamic regression models
Dynamic sparsity on dynamic regression models
Paloma W. Uribe
H. Lopes
23
17
0
29 Sep 2020
Inference in Bayesian Additive Vector Autoregressive Tree Models
Inference in Bayesian Additive Vector Autoregressive Tree Models
Florian Huber
Luca Rossini
73
23
0
29 Jun 2020
Bayesian forecasting of multivariate time series: Scalability, structure
  uncertainty and decisions
Bayesian forecasting of multivariate time series: Scalability, structure uncertainty and decisions
M. West
BDLAI4TS
76
46
0
21 Nov 2019
Fast and Flexible Bayesian Inference in Time-varying Parameter
  Regression Models
Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models
Niko Hauzenberger
Florian Huber
Gary Koop
Luca Onorante
AI4TS
91
37
0
23 Oct 2019
Shrinkage in the Time-Varying Parameter Model Framework Using the R
  Package shrinkTVP
Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP
Peter Knaus
Angela Bitto-Nemling
A. Cadonna
Sylvia Fruhwirth-Schnatter
108
22
0
16 Jul 2019
Horseshoe Regularization for Machine Learning in Complex and Deep Models
Horseshoe Regularization for Machine Learning in Complex and Deep Models
A. Bhadra
J. Datta
Yunfan Li
Nicholas G. Polson
87
15
0
24 Apr 2019
Bayesian dynamic variable selection in high dimensions
Bayesian dynamic variable selection in high dimensions
Gary Koop
Dimitris Korobilis
57
39
0
09 Sep 2018
Sophisticated and small versus simple and sizeable: When does it pay off
  to introduce drifting coefficients in Bayesian VARs?
Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?
Martin Feldkircher
Luis Gruber
Florian Huber
G. Kastner
68
8
0
01 Nov 2017
Sparse Bayesian vector autoregressions in huge dimensions
Sparse Bayesian vector autoregressions in huge dimensions
G. Kastner
Florian Huber
76
95
0
11 Apr 2017
Sparse Bayesian time-varying covariance estimation in many dimensions
Sparse Bayesian time-varying covariance estimation in many dimensions
G. Kastner
70
102
0
30 Aug 2016
Should I stay or should I go? A latent threshold approach to large-scale
  mixture innovation models
Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models
Florian Huber
G. Kastner
Martin Feldkircher
54
43
0
15 Jul 2016
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