Trending Research
A User-Focused Approach to Evaluating Probabilistic and Categorical Forecasts
A user-focused verification approach for evaluating probability forecasts of binary outcomes (also known as probabilistic classifiers) is demonstrated that is (i) based on proper scoring rules, (ii) focuses on user decision thresholds, and (iii) provides actionable insights.
Applications
Stability Selection
Estimation of structure, such as in variable selection, graphical modelling or cluster analysis is notoriously difficult, especially for high-dimensional data.
Methodology
PyDMD: A Python package for robust dynamic mode decomposition
The method's linear algebra-based formulation additionally allows for a variety of optimizations and extensions that make the algorithm practical and viable for real-world data analysis.
Computation Systems and Control Systems and Control Dynamical Systems Computational Physics
StateSpaceModels.jl: a Julia Package for Time-Series Analysis in a State-Space Framework
StateSpaceModels. jl is an open-source Julia package for modeling, forecasting and simulating time series in a state-space framework.
Computation Optimization and Control
Multilevel Delayed Acceptance MCMC
pymc-devs/pymc
•
•
We develop a novel Markov chain Monte Carlo (MCMC) method that exploits a hierarchy of models of increasing complexity to efficiently generate samples from an unnormalized target distribution.
Methodology Computation 62F15, 62M05, 65C05, 65C40
ruptures: change point detection in Python
ruptures is a Python library for offline change point detection.
Computation Mathematical Software
Bambi: A simple interface for fitting Bayesian linear models in Python
The popularity of Bayesian statistical methods has increased dramatically in recent years across many research areas and industrial applications.
Computation
Identification of oscillatory brain networks with Hidden Gaussian Graphical Spectral models of EEG/MEG
A solution of such inverse problems estimates as a first step the activity emerging within functional networks from EEG or MEG data.
Methodology Neurons and Cognition
Conditional forecasting of bus travel time and passenger occupancy with Bayesian Markov regime-switching vector autoregression
xiaoxuchen/markov-regime-switching-model
•
•
In this paper, we develop a Bayesian Markov regime-switching vector autoregressive model to jointly forecast both bus travel time and passenger occupancy with uncertainty.
Applications
Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales
For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum.
Methodology
