Add to ORKGWe propose a new \textit{quadratic programming-based} method of approximating a nonstandard density using a multivariate Gaussian density. Such nonstandard densities usually arise while developing posterior samplers for unobserved components models involving inequality constraints on the parameters. For instance, Chan et al. (2016) provided a new model of trend inflation with linear inequality constraints on the stochastic trend. We implemented the proposed quadratic programming-based method for this model and compared it to the existing approximation. We observed that the proposed method works as well as the existing approximation in terms of the final trend estimates while achieving gains in terms of sample efficiency.Comment: 9 pages, 6 ...
Theoretical constraints on economic-model parameters often are in the form of inequality restriction...
International audienceIntroducing inequality constraints in Gaussian process (GP) models can lead to...
International audienceIntroducing inequality constraints in Gaussian process (GP) models can lead to...
The standard Kalman filter cannot handle inequality constraints imposed on the state variables, as s...
The standard Kalman filter cannot handle inequality constraints imposed on the state variables, as s...
Theoretical constraints on economic model parameters often are in the form of inequality restriction...
In a previous article, a least square regression estimation procedure was proposed: first, we condis...
Theoretical constraints on economic-model parameters often are in the form of inequality restriction...
This paper introduces a new model of trend (or underlying) in‡ation. In contrast to many earlier app...
from the Table of Contents: Introduction; Bias and test size when g(.) is linear; A reduced form tes...
Theoretical constraints on economic model parameters often are in the form of inequality restriction...
In linear models and multivariate normal situations, prior information in linear inequality form may...
In this thesis, I employ a number of machine learning (ML) methods on the inflation forecasting prob...
This is the publisher's version, also available electronically from http://www.economicsbulletin.com...
This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier ap...
Theoretical constraints on economic-model parameters often are in the form of inequality restriction...
International audienceIntroducing inequality constraints in Gaussian process (GP) models can lead to...
International audienceIntroducing inequality constraints in Gaussian process (GP) models can lead to...
The standard Kalman filter cannot handle inequality constraints imposed on the state variables, as s...
The standard Kalman filter cannot handle inequality constraints imposed on the state variables, as s...
Theoretical constraints on economic model parameters often are in the form of inequality restriction...
In a previous article, a least square regression estimation procedure was proposed: first, we condis...
Theoretical constraints on economic-model parameters often are in the form of inequality restriction...
This paper introduces a new model of trend (or underlying) in‡ation. In contrast to many earlier app...
from the Table of Contents: Introduction; Bias and test size when g(.) is linear; A reduced form tes...
Theoretical constraints on economic model parameters often are in the form of inequality restriction...
In linear models and multivariate normal situations, prior information in linear inequality form may...
In this thesis, I employ a number of machine learning (ML) methods on the inflation forecasting prob...
This is the publisher's version, also available electronically from http://www.economicsbulletin.com...
This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier ap...
Theoretical constraints on economic-model parameters often are in the form of inequality restriction...
International audienceIntroducing inequality constraints in Gaussian process (GP) models can lead to...
International audienceIntroducing inequality constraints in Gaussian process (GP) models can lead to...