Solving, Estimating and Selecting Nonlinear Dynamic Models without the Curse of Dimensionality

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. TheSmolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the model solution. The operator also eliminates the curse from Gaussian quadrature and we use it for the integrals arising from rational expectations and in three new nonlinear state space filters. The filters substantially decrease the computational burden compared to the sequential importance resampling particle filter. The posterior of the structural parameters is estimated by a new Metropolis-Hastings algorithm with mixing parallel sequences. The parallel extension improves the global maximization property of the algorithm, simplifies the choice of the innovation variances, allows for unbiased convergence diagnostics and for a simple implementation of the estimation on parallel computers. Finally, we provide all algorithms in the open source software JBendge4 for the solution and estimation of a general class of models.Dynamic Stochastic General Equilibrium (DSGE) Models, Bayesian Time Series Econometrics, Curse of Dimensionality

JBendge: An Object-Oriented System for Solving, Estimating and Selecting Nonlinear Dynamic Models

We present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The imple- mented solution methods for nding the unknown policy function are the standard linearization around the deterministic steady state, and a function iterator using a multivariate global Chebyshev polynomial approximation with the Smolyak op- erator to overcome the course of dimensionality. The operator is also useful for numerical integration and we use it for the integrals arising in rational expecta- tions and in nonlinear state space lters. The estimation step is done by a parallel Metropolis-Hastings (MH) algorithm, using a linear or nonlinear lter. Implemented are the Kalman, Extended Kalman, Particle, Smolyak Kalman, Smolyak Sum, and Smolyak Kalman Particle lters. The MH sampling step can be interactively moni- tored and controlled by sequence and statistics plots. The number of parallel threads can be adjusted to benet from multiprocessor environments. JBendge is based on the framework JStatCom, which provides a standardized ap- plication interface. All tasks are supported by an elaborate multi-threaded graphical user interface (GUI) with project management and data handling facilities.Dynamic Stochastic General Equilibrium (DSGE) Models, Bayesian Time Series Econometrics, Java, Software Development

A software framework for data based analysis

Es wird das Software Framework JStatCom vorgestellt, welches die Enwicklung von leistungsfähigen grafischen Benutzerschnittstellen für Daten-basierte Analysemethoden wesentlich vereinfacht, wobei der Schwerpunkt auf Methoden der Ökonometrie, insbesondere der Zeitreihenanalyse liegt. Das Konzept besteht darin, sämtliche wiederkehrenden Aufgaben mit Hilfe von Java-Klassen zu lösen, sowie die Ausführung von speziellen Algorithmen an externe Programme, wie z.B. Gauss oder Matlab, zu delegieren. Auf diese Weise können schon existierende Prozeduren aus verschiedenen Programmiersprachen wiederverwendet werden. Weiterhin wird die ökonometrische Anwendungssoftware JMulTi beschrieben, die auf Basis dieses Frameworks erstellt wurde.This work presents the software framework JStatCom which is geared towards the development of powerful graphical user interfaces for data based analysis methods, especially for econometrics and time series analysis. The concept is to solve all recurring tasks with the help of Java classes and to delegate the execution of special algorithms to external programs, for example Gauss or Matlab. This way it is possible to reuse already existing procedures written in different programming languages. Furthermore, the econometric software JMulTi will be presented which has been developed with the help of this framework

JBendge

We present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The imple- mented solution methods for finding the unknown policy function are the standard linearization around the deterministic steady state, and a function iterator using a multivariate global Chebyshev polynomial approximation with the Smolyak op- erator to overcome the course of dimensionality. The operator is also useful for numerical integration and we use it for the integrals arising in rational expecta- tions and in nonlinear state space filters. The estimation step is done by a parallel Metropolis-Hastings (MH) algorithm, using a linear or nonlinear filter. Implemented are the Kalman, Extended Kalman, Particle, Smolyak Kalman, Smolyak Sum, and Smolyak Kalman Particle filters. The MH sampling step can be interactively moni- tored and controlled by sequence and statistics plots. The number of parallel threads can be adjusted to benefit from multiprocessor environments. JBendge is based on the framework JStatCom, which provides a standardized ap- plication interface. All tasks are supported by an elaborate multi-threaded graphical user interface (GUI) with project management and data handling facilities

Solving, Estimating and Selecting Nonlinear Dynamic Models without the Curse of Dimensionality

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the model solution. The operator also eliminates the curse from Gaussian quadrature and we use it for the integrals arising from rational expectations and in three new nonlinear state space filters. The filters substantially decrease the computational burden compared to the sequential importance resampling particle filter. The posterior of the structural parameters is estimated by a new Metropolis-Hastings algorithm with mixing parallel sequences. The parallel extension improves the global maximization property of the algorithm, simplifies the choice of the innovation variances, allows for unbiased convergence diagnostics and for a simple implementation of the estimation on parallel computers. Finally, we provide all algorithms in the open source software JBendge4 for the solution and estimation of a general class of models

Humboldt-Universität zu Berlin

Zusammenfassung Es wird das Software Framework JStatCom vorgestellt, welches die Enwick-lung von leistungsfähigen grafischen Benutzerschnittstellen für Daten-basierte Analysemethoden wesentlich vereinfacht, wobei der Schwerpunkt auf Methoden der Ökonometrie, insbesondere der Zeitreihenanalyse liegt. Das Konzept besteh

Accessory heterozygous mutations in cone photoreceptor CNGA3 exacerbate CNG channel\textendashassociated retinopathy

International audienceMutations in CNGA3 and CNGB3, the genes encoding the subunits of the tetrameric cone photoreceptor cyclic nucleotide–gated ion channel, cause achromatopsia, a congenital retinal disorder characterized by loss of cone function. However, a small number of patients carrying the CNGB3/c.1208G>A;p.R403Q mutation present with a variable retinal phenotype ranging from complete and incomplete achromatopsia to moderate cone dysfunction or progressive cone dystrophy. By exploring a large patient cohort and published cases, we identified 16 unrelated individuals who were homozygous or (compound-)heterozygous for the CNGB3/c.1208G>A;p.R403Q mutation. In-depth genetic and clinical analysis revealed a co-occurrence of a mutant CNGA3 allele in a high proportion of these patients (10 of 16), likely contributing to the disease phenotype. To verify these findings, we generated a Cngb3R403Q/R403Q mouse model, which was crossbred with Cnga3-deficient (Cnga3–/–) mice to obtain triallelic Cnga3+/– Cngb3R403Q/R403Q mutants. As in human subjects, there was a striking genotype-phenotype correlation, since the presence of 1 Cnga3-null allele exacerbated the cone dystrophy phenotype in Cngb3R403Q/R403Q mice. These findings strongly suggest a digenic and triallelic inheritance pattern in a subset of patients with achromatopsia/severe cone dystrophy linked to the CNGB3/p.R403Q mutation, with important implications for diagnosis, prognosis, and genetic counseling

Accessory heterozygous mutations in cone photoreceptor CNGA3 exacerbate CNG channel–associated retinopathy

Mutations in CNGA3 and CNGB3, the genes encoding the subunits of the tetrameric cone photoreceptor cyclic nucleotide-gated ion channel, cause achromatopsia, a congenital retinal disorder characterized by loss of cone function. However, a small number of patients carrying the CNGB3/c.1208G>A;p.R403Q mutation present with a variable retinal phenotype ranging from complete and incomplete achromatopsia to moderate cone dysfunction or progressive cone dystrophy. By exploring a large patient cohort and published cases, we identified 16 unrelated individuals who were homozygous or (compound-)heterozygous for the CNGB3/c.1208G>A;p.R403Q mutation. In-depth genetic and clinical analysis revealed a co-occurrence of a mutant CNGA3 allele in a high proportion of these patients (10 of 16), likely contributing to the disease phenotype. To verify these findings, we generated a Cngb3R403Q/R403Q mouse model, which was crossbred with Cnga3-deficient (Cnga3-/-) mice to obtain triallelic Cnga3+/- Cngb3R403Q/R403Q mutants. As in human subjects, there was a striking genotype-phenotype correlation, since the presence of 1 Cnga3-null allele exacerbated the cone dystrophy phenotype in Cngb3R403Q/R403Q mice. These findings strongly suggest a digenic and triallelic inheritance pattern in a subset of patients with achromatopsia/severe cone dystrophy linked to the CNGB3/p.R403Q mutation, with important implications for diagnosis, prognosis, and genetic counseling