Trending Research

Liesel: A Probabilistic Programming Framework for Developing Semi-Parametric Regression Models and Custom Bayesian Inference Algorithms

liesel-devs/liesel 22 Sep 2022

Liesel is a new probabilistic programming framework developed with the aim of supporting research on Bayesian inference based on Markov chain Monte Carlo (MCMC) simulations in general and semi-parametric regression specifications in particular.

Computation

43
0.01 stars / hour

ipd: An R Package for Conducting Inference on Predicted Data

ipd-tools/ipd 12 Oct 2024

Summary: ipd is an open-source R software package for the downstream modeling of an outcome and its associated features where a potentially sizable portion of the outcome data has been imputed by an artificial intelligence or machine learning (AI/ML) prediction algorithm.

Methodology Computation

7
0.01 stars / hour

Functional Singular Value Decomposition

Jianbin-Tan/Functional-Singular-Value-Decompostion 4 Oct 2024

To uncover the statistical structures of such data, we propose Functional Singular Value Decomposition (FSVD), a unified framework encompassing various tasks for the analysis of functional data with potential heterogeneity.

Methodology Statistics Theory Applications Computation Statistics Theory

5
0.01 stars / hour

The Barker proposal: combining robustness and efficiency in gradient-based MCMC

UCL/rmcmc 11 May 2020

There is a tension between robustness and efficiency when designing Markov chain Monte Carlo (MCMC) sampling algorithms.

Computation Methodology

4
0.01 stars / hour

Ball: An R package for detecting distribution difference and association in metric spaces

Mamba413/Ball 9 Nov 2018

The rapid development of modern technology facilitates the appearance of numerous unprecedented complex data which do not satisfy the axioms of Euclidean geometry, while most of the statistical hypothesis tests are available in Euclidean or Hilbert spaces.

Computation

29
0.01 stars / hour

How often does the best team win? A unified approach to understanding randomness in North American sport

bigfour/competitiveness 21 Jan 2017

Statistical applications in sports have long centered on how to best separate signal (e. g. team talent) from random noise.

Applications

20
0.01 stars / hour

The statistical finite element method (statFEM) for coherent synthesis of observation data and model predictions

alan-turing-institute/stat-fem 15 May 2019

From the outset, we postulate a data-generating model which additively decomposes data into a finite element, a model misspecification and a noise component.

Methodology Numerical Analysis Numerical Analysis

13
0.01 stars / hour

Bayesian Median Autoregression for Robust Time Series Forecasting

xylimeng/BayesMAR 4 Jan 2020

We develop a Bayesian median autoregressive (BayesMAR) model for time series forecasting.

Applications Econometrics Methodology

7
0.01 stars / hour

MGM: Estimating Time-Varying Mixed Graphical Models in High-Dimensional Data

jmbh/mgm 23 Oct 2015

We present the R-package mgm for the estimation of k-order Mixed Graphical Models (MGMs) and mixed Vector Autoregressive (mVAR) models in high-dimensional data.

Applications

28
0.01 stars / hour

Estimating Psychological Networks and their Accuracy: A Tutorial Paper

sachaepskamp/bootnet 20 Jan 2017

Finally, we developed the free R-package bootnet that allows for estimating psychological networks in a generalized framework in addition to the proposed bootstrap methods.

Applications Methodology

32
0.01 stars / hour