Keywords
Monte Carlo methodStatisticsStatistical physicsMathematicsMonte Carlo method in statistical physicsEconometricsHybrid Monte CarloComputer scienceMarkov chain Monte CarloPhysics
Affiliated Institutions
Related Publications
CODA: convergence diagnosis and output analysis for MCMC
[1st paragraph] At first sight, Bayesian inference with Markov Chain Monte Carlo (MCMC) appears to be straightforward. The user defines a full probability model, perhaps using o...
Smooth Skyride through a Rough Skyline: Bayesian Coalescent-Based Inference of Population Dynamics
Kingman's coalescent process opens the door for estimation of population genetics model parameters from molecular sequences. One paramount parameter of interest is the effective...
MCMC Methods for Multi-Response Generalized Linear Mixed Models: The<b>MCMCglmm</b><i>R</i>Package
Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot be obtained in clo...
Comparative Performance of Bayesian and AIC-Based Measures of Phylogenetic Model Uncertainty
Reversible-jump Markov chain Monte Carlo (RJ-MCMC) is a technique for simultaneously evaluating multiple related (but not necessarily nested) statistical models that has recentl...
The Bayesian Approach to Radiocarbon Calibration Curve Estimation: The IntCal13, Marine13, and SHCal13 Methodologies
This article outlines the Bayesian models and methods used to facilitate construction of the 2013 internationally agreed radiocarbon calibration curves known as IntCal13, Marine...
Publication Info
- Year
- 1968
- Type
- article
- Volume
- 33
- Issue
- 1
- Pages
- 37-71
- Citations
- 162
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
162
OpenAlex
Cite This
Robert L. Linn
(1968).
A Monte Carlo Approach to the Number of Factors Problem.
Psychometrika
, 33
(1)
, 37-71.
https://doi.org/10.1007/bf02289675
Identifiers
- DOI
- 10.1007/bf02289675