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Identifying Co-occurring Neighbourhood Environmental Patterns and Their Association with Health Behaviours in a Dutch Urban Population at High Cardiometabolic Risk

Smit AK, Vos RC, Velde LAvd, Haas MR, Numans ME, Beenackers MA, Bonten TN, Jong JCK.   +7 more
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Expansions for Log Densities of Multivariate Estimates

Methodology and Computing in Applied Probability, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Withers, Christopher S., Nadarajah, Saralees   +1 more
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Feasibility of Multivariate Density Estimates

Biometrika, 1991
SUMMARY The 'curse of dimensionality' has been interpreted as suggesting that kernel methods have limited applicability in more than several dimensions. In this note, qualitative and quantitative performance measures for multivariate density estimates are examined. Optimal pointwise and global window widths for mean absolute and mean squared errors are
David W. Scott, M. P. Wand
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Exponential Series Estimator of multivariate densities

Journal of Econometrics, 2007
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Multivariate locally adaptive kernel density estimation

Communications in Statistics - Simulation and Computation, 2021
When the underlying density exhibits multiple modes with different scales and orientations, density estimators with locally adaptive smoothing parameters show substantial gains over those with fixe...
Jia-Xing Gao, Daquan Jiang, Minping Qian
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Multivariate Density Estimation by Neural Networks

IEEE Transactions on Neural Networks and Learning Systems
We propose nonparametric methods to obtain the Probability Density Function (PDF) to assess the properties of the underlying data generating process (DGP) without imposing any assumptions on the DGP, using neural networks (NNs). The proposed NN has advantages compared to well-known parametric and nonparametric density estimators. Our approach builds on
Dewi E. W. Peerlings, Jan A. van den Brakel, Nalan Bastürk, Marco J. H. Puts   +3 more
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Structured estimation, II: Multivariate probability density estimation

IEEE Transactions on Information Theory, 1981
We continue the research begun in 1975 on structured estimation. The original work in 1976 by Morgera and Cooper dealt with the Gaussian two-category classification problem when the common covariance matrix is unknown and must be estimated in order to approximate the hyperplane for decisionmaking, which is optimum for the true covariance matrix.
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Multivariate density estimation

2015
In traditional applied econometric settings, we typically have access to several variables. For example, in our growth example presented in Chapter 2, not only would a typical analysis have access to output per worker, but also physical and human capital stocks, measures of corruption, natural resource levels, institutional quality, and perhaps many ...
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