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Full-Text Articles in Statistics and Probability
Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila
Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila
Faculty Publications
This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …
Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill
Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill
Faculty Publications
Purpose — This paper aims to examine whether changing the clustering of countries within a United States Combatant Command (COCOM) area of responsibility promotes improved forecasting of conflict. Design/methodology/approach — In this paper statistical learning methods are used to create new country clusters that are then used in a comparative analysis of model-based conflict prediction. Findings — In this study a reorganization of the countries assigned to specific areas of responsibility are shown to provide improvements in the ability of models to predict conflict. Research limitations/implications — The study is based on actual historical data and is purely data driven. …
Unrestricted Factor Analysis: A Powerful Alternative To Confirmatory Factor Analysis, Jan-Benedict E.M. Steenkamp, Alberto Maydeu-Olivares
Unrestricted Factor Analysis: A Powerful Alternative To Confirmatory Factor Analysis, Jan-Benedict E.M. Steenkamp, Alberto Maydeu-Olivares
Faculty Publications
The gold standard for modeling multiple indicator measurement data is confirmatory factor analysis (CFA), which has many statistical advantages over traditional exploratory factor analysis (EFA). In most CFA applications, items are assumed to be pure indicators of the construct they intend to measure. However, despite our best efforts, this is often not the case. Cross-loadings incorrectly set to zero can only be expressed through the correlations between the factors, leading to biased factor correlations and to biased structural (regression) parameter estimates. This article introduces a third approach, which has emerged in the psychometric literature, viz., unrestricted factor analysis (UFA). UFA …