Multistage plug—in bandwidth selection for kernel distribution function estimates

By Alan M. Polansky, E. Baker. 2000

100 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a331af1c62ad8f31e2e3d9f7a74111ff7328bce7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. P. Mujumdar
2. Subhankar Karmakar
3. Subimal Ghosh
4. Slobodan P. Simonovic

In Control and Systems Engineering

1. P. Mujumdar
2. Subhankar Karmakar
3. Subimal Ghosh
4. Slobodan P. Simonovic

In Statistics and Probability

1. P. Mujumdar
2. Subhankar Karmakar
3. Subimal Ghosh
4. Slobodan P. Simonovic

Citations in the corpus

• THE CONTROL CHART FOR INDIVIDUAL OBSERVATIONS FROM A MULTIVARIATE NON-NORMAL DISTRIBUTION (2001, background): “The kernel estimator of the T2 distribution, FK, can be written as FKðyÞ ¼ n 1 Xn j¼1 fðy T2j Þ=hg, ð6Þ where outlined in Polansky and Baker [10], entails lengthy calculations in three steps.”
• Bivariate flood frequency analysis: Part 1. Determination of marginals by parametric and nonparametric techniques (2008, methodology): “Plug-in estimates (Polansky and Baker, 2000) and least-squares cross-validation (Scott, 1992; Tarboton et al.”
• Nonparametric methods for modeling GCM and scenario uncertainty in drought assessment (2007, methodology): “Although there are other methods like plug-in estimates [ Polansky and Baker, 2000 ] and least squares cross validation [Scott, 1992; Tarboton et al., 1998], in the present study the bandwidth is estimated based on normal distribution for computational simplicity at each of the time steps.”