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Simulation-based Estimation Methods for Financial Time Series Models [PDF]

This chapter overviews some recent advances on simulation-based methods of estimating financial time series models that are widely used in financial economics.
Jun Yu
core  

Comparison of Machine-learning and Bayesian Inferences for the Interior of Rocky Exoplanets with Large Compositional Diversity

The Astrophysical Journal Supplement Series
In previous work, we demonstrated that machine-learning techniques based on mixture density networks (MDNs) are successful in inferring the interior structure of rocky exoplanets with large compositional diversity.
Yong Zhao, Zibo Liu, Dongdong Ni, Zhiyuan Chen   +3 more
doaj   +1 more source

MALAYSIAN COMMUNICATION AND MULTIMEDIA COMMISSION'S (MCMC) LAW ENFORCEMENT SPECTRUM: EXPLORING ARREST AUTHORITY

Malaysian Journal of Syariah and Law
The Malaysian Communications and Multimedia Commission (MCMC) regulates multimedia and communication activities and plays a role in protecting consumers from harms such as online scams and digital fraud.
Mimi Sofiah Ahmad Mustafa, Yuhanza Othman, Nasihah Naimat, Ida Rahayu Mahat, Marziana Abd Malib, Mohd Ab Malek Md Shah, Muhammad Arif Haron   +6 more
doaj   +1 more source

A combined Markov Chain Monte Carlo and Levenberg–Marquardt inversion method for heterogeneous subsurface reservoir modeling

Discover Applied Sciences
In this study, we systematically investigate an inverse method for heterogeneous porous media to obtain porosity and permeability fields considering only production well data. The forward modeling of the input data, namely pressure and saturation fields,
Jarbas A. Fernandes, Juarez S. Azevedo, Saulo P. Oliveira   +2 more
doaj   +1 more source

Supervised Frequency Change Detection Using Mcmc Methods

, 2015
Publication in the conference proceedings of EUSIPCO, Tampere, Finland ...
Hitti, Eric, DONCARLI, Christian, LUCAS, Marie-Francoise   +2 more
openaire   +1 more source

Practical guidelines for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) [version 3; peer review: 3 approved, 1 approved with reservations]

Open Research Europe
Phylogenetic estimation is, and has always been, a complex endeavor. Estimating a phylogenetic tree involves evaluating many possible solutions and possible evolutionary histories that could explain a set of observed data, typically by using a model of ...
Orlando Schwery, Joëlle Barido-Sottani, Chi Zhang, Rachel C. M. Warnock, April Marie Wright   +4 more
doaj   +1 more source

Practical guidelines for Bayesian phylogenetic inference using Markov Chain Monte Carlo (MCMC) [version 2; peer review: 3 approved, 1 approved with reservations]

Open Research Europe
Phylogenetic estimation is, and has always been, a complex endeavor. Estimating a phylogenetic tree involves evaluating many possible solutions and possible evolutionary histories that could explain a set of observed data, typically by using a model of ...
Orlando Schwery, Joëlle Barido-Sottani, Chi Zhang, Rachel C. M. Warnock, April Marie Wright   +4 more
doaj   +1 more source

An MCMC Approach to Bayesian Image Analysis in Fourier Space

Data Science in Science
Bayesian image analysis methods are commonly applied to solve image analysis problems such as noise reduction, feature enhancement, and object detection.
Konstantinos Bakas, John Kornak, Hernando Ombao   +2 more
doaj   +1 more source

Joint delay–Doppler estimation for passive bistatic radar with direct-path interference using MCMC method

, 2018
Yongsheng Zhao, Yongjun Zhao, Chuang Zhao   +2 more
semanticscholar   +1 more source

boa: An R Package for MCMC Output Convergence Assessment and Posterior Inference

Journal of Statistical Software, 2007
Markov chain Monte Carlo (MCMC) is the most widely used method of estimating joint posterior distributions in Bayesian analysis. The idea of MCMC is to iteratively produce parameter values that are representative samples from the joint posterior.
Brian J. Smith
doaj