Results 201 to 210 of about 112,632 (333)

The Time‐Varying Anchoring of Inflation Expectations in Australia

Australian Economic Review, EarlyView.
ABSTRACT This paper examines the anchoring of inflation expectations in Australia, an important indicator of the Reserve Bank of Australia's (RBA) credibility in the public's eyes regarding its inflation mandate. Rather than treating anchoring as a binary state, the study examines its evolution over time.
Thuy Hang Duong
wiley   +1 more source

Gradient boosting: A computationally efficient alternative to Markov chain Monte Carlo sampling for fitting large Bayesian spatio-temporal binomial regression models. [PDF]

Infect Dis Model
Huang R, McMahan C, Herrin B, McLain A, Cai B, Self S.   +5 more
europepmc   +1 more source

On variable splitting for Markov chain Monte Carlo [PDF]

, 2019
Maxime Vono, Nicolas Dobigeon, Pierre Chainais   +2 more
openalex  

A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces

Statistics and computing, 2006
C. Braak
semanticscholar   +1 more source

Chromosome‐scale genome assembly of the South American fruit fly, Anastrepha fraterculus sp.1

Insect Science, EarlyView.
Anastrepha fraterculus sp. 1 is a major fruit fly pest in Argentina, currently controlled through chemical treatments and traps. This study aims to enhance the genomic understanding of this species to support the development of sterile insect technique as well as the use of innovative technologies.
Máximo Rivarola, Claudia A. Conte, Pierre Berube, Shu‐Huang Chen, M. Cecilia Giardini, Alejandra C. Scannapieco, Fabián H. Milla, María C. Soria, Romina M. Russo, Juan P. Wulff, Haig H. Djambazian, Rolando R. Pomar, Alfred M. Handler, Kostas Bourtzis, Ioannis Ragoussis, Silvia B. Lanzavecchia   +15 more
wiley   +1 more source

Predicting Colloidal Interaction Parameters from Small-Angle X-ray Scattering Curves Using Artificial Neural Networks and Markov Chain Monte Carlo Sampling. [PDF]

JACS Au
Wong K, Qi R, Yang Y, Luo Z, Guldin S, Butler KT.   +5 more
europepmc   +1 more source

Empirical evaluation of normalizing flows in Markov Chain Monte Carlo [PDF]

David Nabergoj, Erik Štrumbelj
openalex   +1 more source

Accelerating delayed-acceptance Markov chain Monte Carlo algorithms [PDF]

, 2018
Samuel Wiqvist, Umberto Picchini, Julie Lyng Forman, Lindorff-Larsen, Kresten, Boomsma, Wouter   +4 more
openalex   +1 more source

Comparative Population Genetics of Two Alvinocaridid Shrimp Species in Chemosynthetic Ecosystems of the Western Pacific

Integrative Zoology, EarlyView.
Little is known about the population divergence and gene flow of deep‐sea animals living in disjunct hydrothermal vents and cold seep habitats. Taking advantage of samples collected from multiple cruises across a huge distance of >5000 km, we revealed the differential population divergence pattern and gene flow in two congeneric species of shrimps ...
Qi Dai, Ting Xu, Yixuan Li, Yanan Sun, Yitao Lin, Takuya Yahagi, Maeva Perez, Pei‐Yuan Qian, Jian‐Wen Qiu   +8 more
wiley   +1 more source

Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling

, 2009
J. Vrugt, C. Braak, C. Diks, B. Robinson, J. Hyman, D. Higdon   +5 more
semanticscholar   +1 more source