Criminal Trajectory Clustering
Criminal trajectory clustering is the broad family of methods that group individuals by the shape of their longitudinal offending curves. Rather than committing to a single statistical model, it spans algorithmic approaches — k-means for longitudinal data, distance-based clustering of trajectory shapes, and likelihood-based latent class growth — and treats the choice of clustering method itself as a modeling decision validated by fit and stability criteria.
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Kilder
- Nagin, D. S. (2005). Group-Based Modeling of Development. Harvard University Press. ISBN: 9780674016866
- Genolini, C., & Falissard, B. (2010). KmL: k-means for longitudinal data. Computational Statistics, 25(2), 317–328. DOI: 10.1007/s00180-009-0178-4 ↗
Sådan citerer du denne side
ScholarGate. (2026, June 22). Clustering of Criminal Offending Trajectories. ScholarGate. https://scholargate.app/da/criminology/criminal-trajectory-clustering
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- Age-Crime Curve ModelingCriminology↔ sammenlign
- Criminal Career ParadigmCriminology↔ sammenlign
- Group-Based Trajectory ModelCriminology↔ sammenlign
- Life-Course Criminology AnalysisCriminology↔ sammenlign
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