SWARM is a cloud platform aimed at improving analytical reasoning in intelligence work. SWARM tries to improve analytical reasoning by improving collaboration within groups of analysts rather than by trying to structure their thinking in any particular way.
- Robust and stochastic optimization
- Convex analysis
- Linear programming
- Monte Carlo simulation
- Model-based estimation
- Matrix algebra review
- Probability and statistics basics
This article is divided into three parts: the first part explains the definition of the economically dependent self-employed and proposes ideas for improving this definition of this dependency. The second part of this article is dedicated to the working conditions of the self-employed, while the last part compares the job satisfaction of the self-employed, employees and family workers.
The Costs of War Project is a team of 35 scholars, legal experts, human rights practitioners, and physicians, which began its work in 2011. We use research and a public website to facilitate debate about the costs of the post-9/11 wars in Iraq, Afghanistan, and Pakistan.
The NLEstimate macro allows you to estimate one or more linear or nonlinear combinations of parameters from any model for which you can save the model parameters and their variance-covariance matrix. Most modeling procedures which offer ESTIMATE, CONTRAST, or LSMEANS statements only provide for estimating or testing linear combinations of model parameters. However, common estimation problems often involve nonlinear combinations, particularly in generalized models with nonidentity link functions such as logistic and Poisson models.
M. Rosen-Zvi, T. Griffiths, M. Steyvers, and P. Smyth. Proceedings of the 20th conference on Uncertainty in artificial intelligence, page 487--494. Arlington, VA, USA, AUAI Press, (2004)