Results 251 to 260 of about 5,912,392 (297)

Approaches on crowd counting and density estimation: a review

Pattern Analysis and Applications, 2021
Bo Li, Hongbo Huang, Ang Zhang, Pei-Chi Liu, Chengfeng Liu   +4 more
semanticscholar   +1 more source

Conditional density estimation

Statistical Modeling Using Local Gaussian Approximation, 2022
D. Tjøstheim, Håkon Otneim, Bård Støve   +2 more
semanticscholar   +1 more source

Multivariate Density Estimation, Theory, Practice and Visualization

Wiley Series in Probability and Statistics, 1992
D. W. Scott
semanticscholar   +2 more sources

SUBSAMPLING FOR DENSITY ESTIMATION

Statistics & Risk Modeling, 2002
Summary: We consider nonparametric density estimation from the point of view of coverage probability. To take into account the problem of bias in bootstrapping nonparametric density kernel estimators, \textit{P. Hall} [Statistics 22, No. 2, 215-232 (1991; Zbl 0809.62031); Ann. Stat. 20, No. 2, 675-694 (1992; Zbl 0748.62028)] showed that it is better to
openaire   +2 more sources

Density Estimation.

The Journal of the Operational Research Society, 1986
Chris Beaumont, B. W. Silverman
openaire   +2 more sources

Bayesian density estimation via dirichlet density processes

Journal of Nonparametric Statistics, 1996
For the purpose of nonparametric density estimation, a prior distribution is constructed on the space of stepwise constant density functions, not necessarily of bounded support. In particular, the sequence of heights is conditionally distributed a priorias a Dirichlet process on the integers, given a bidimensional mixing parameter.
openaire   +2 more sources

Density Estimation for Statistics and Data Analysis

, 1987
Bernard Walter Silverman
semanticscholar   +1 more source

Model-Based Clustering, Discriminant Analysis, and Density Estimation

, 2002
C. Fraley, A. Raftery
semanticscholar   +1 more source

VARIABLE KERNEL DENSITY ESTIMATES AND VARIABLE KERNEL DENSITY ESTIMATES

Australian Journal of Statistics, 1990
SummaryThe term “variable kernel density estimate” is sometimes used to mean a kernel density estimate employing a different bandwidth for each data point, and sometimes to denote a kernel density estimate with bandwidth a function of estimation location.
openaire   +1 more source

Bayesian Density Estimation and Inference Using Mixtures

, 1995
M. Escobar, M. West
semanticscholar   +1 more source