Improving density estimation by incorporating spatial information

Eurasip Journal on Advances in Signal Processing

Volumn 2010, Issue , 2010, Pages

  Smith, Laura M ^a   Keegan, Matthew S ^a   Wittman, Todd ^a   Mohler, George O ^a   Bertozzi, Andrea L ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APRIORI; DATA SETS; DENSITY ESTIMATES; DENSITY ESTIMATION; DISCRETE EVENTS; GEOGRAPHIC INFORMATION; GEOGRAPHIC LOCATION; GEOGRAPHICAL INFORMATION; HIGH RESOLUTION; HOUSING DENSITY; KERNEL DENSITY ESTIMATION; MAXIMUM PENALIZED LIKELIHOOD; PROBABILITY DENSITIES; RELATIVE PROBABILITY; SATELLITE IMAGES; SOBOLEV NORMS; SPATIAL DATA; SPATIAL INFORMATIONS; SPATIAL REGIONS; TOTAL VARIATION;

ESTIMATION; LANDFORMS; OCEANOGRAPHY; PROBABILITY; PROBABILITY DENSITY FUNCTION; SECURITY OF DATA;

MAXIMUM LIKELIHOOD ESTIMATION;

EID: 77955300837     PISSN: 16876172     EISSN: 16876180     Source Type: Journal    
DOI: 10.1155/2010/265631     Document Type: Article

References (20)

1. Kim Rossmo D., Geographic Profiling 2000 CRC Press
2. Mohler G. O., Short M. B., Geographic profiling from kinetic models of criminal behavior. in review
3. O'Leary M., The mathematics of geographic profiling Journal of Investigative Psychology and Offender Profiling 2009 6 253 265
4. Silverman B. W., Kernel density estimation using the fast fourier transform Applied Statistics, Royal Statistical Society 1982 31 93 97
5. Silverman B. W., Density Estimation for Statistics and Data Analysis 1986 Chapman Hall/CRC
6. Davies P. L., Kovac A., Densities, spectral densities and modality Annals of Statistics 2004 32 3 1093 1136
7. Kooperberg C., Stone C. J., A study of logspline density estimation Computational Statistics and Data Analysis 1991 12 3 327 347
8. Sardy S., Tseng P., Density estimation by total variation penalized likelihood driven by the sparsity l 1 information criterion Scandinavian Journal of Statistics 2010 37 2 321 337
9. Koenker R., Mizera I., Density estimation by total variation regularization Advances in Statistical Modeling and Inference 2007 World Scientific 613 634 Essays in Honor of Kjell A. Doksum
10. Mohler G. O., Bertozzi A. L., Goldstein T. A., Osher S. J., Fast TV regularization for 2D maximum penalized likelihood estimation. to appear in Journal of Computational and Graphical Statistics
11. Eggermont P. P. B., LaRiccia V. N., Maximum Penalized Likelihood Estimation 2001 Berlin, Germany Springer
12. Goodd I. J., Gaskins R. A., Nonparametric roughness penalties for probability densities Biometrika 1971 58 2 255 277
13. Rudin L. I., Osher S., Fatemi E., Nonlinear total variation based noise removal algorithms Physica D 1992 60 14 259 268
14. Moeller M., Wittman T., Bertozzi A. L., Variational wavelet pan-sharpening CAM Report 2008 08-81 UCLA
15. Ballester C., Caselles V., Igual L., Verdera J., Roug B., A variational model for P + XS image fusion International Journal of Computer Vision 2006 69 1 43 58
16. Mumford D., Shah J., Optimal approximations by piecewise smooth functions and associated variational problems Communications on Pure and Applied Mathematics 1989 42 5 577 685
17. Ambrosio L., Tortorelli V. M., Approximation of functional depending on jumps by elliptic functional via -convergence Communications on Pure and Applied Mathematics 1990 43 8 999 1036
18. Osher S., Burger M., Goldfarb D., Xu J., Yin W., An iterative regularization method for total variation-based image restoration Multiscale Modeling and Simulation 2005 4 2 460 489
19. Goldstein T., Osher S., Split bregman method for L1 regularized problems SIAM Journal on Imaging Sciences 2009 2 323 343
20. Wang Y., Yang J., Yin W., Zhang Y., A new alternating minimization algorithm for total variation image reconstruction SIAM Journal on Imaging Sciences 2008 1 3 248 272