Comparison of linear and nonlinear dimension reduction techniques for automated process monitoring of a decentralized wastewater treatment facility

K Kazor, RW Holloway, TY Cath, AS Hering - … environmental research and …, 2016 - Springer
Multivariate statistical methods for online process monitoring have been widely applied to
chemical, biological, and engineered systems. While methods based on principal …

Novel kernel density estimator based on ensemble unbiased cross-validation

YL He, X Ye, DF Huang, JZ Huang, JH Zhai - Information Sciences, 2021 - Elsevier
Unbiased cross-validation (UCV) is a commonly-used method to calculate the optimal
bandwidth for the kernel density estimator (KDE), which estimates the underlying probability …

[HTML][HTML] A novel method for the homogenization of daily temperature series and its relevance for climate change analysis

A Toreti, FG Kuglitsch, E Xoplaki… - Journal of …, 2010 - journals.ametsoc.org
Instrumental daily series of temperature are often affected by inhomogeneities. Several
methods are available for their correction at monthly and annual scales, whereas few exist …

Optimal sampling for density estimation in continuous time

D Blanke, B Pumo - Journal of Time Series Analysis, 2003 - Wiley Online Library
Optimal sampling for density estimation in continuous time - Blanke - 2003 - Journal of Time
Series Analysis - Wiley Online Library Skip to Article Content Skip to Article Information Wiley …

A kernel mode estimate under random left truncation and time series model: asymptotic normality

O Benrabah, E Ould Saïd, A Tatachak - Statistical Papers, 2015 - Springer
Abstract Let\left {Y_ N, N ≥ 1\right\} YN, N≥ 1 be a sequence of random variables of interest
and\left {T_ N, N ≥ 1\right\} TN, N≥ 1 be a sequence of truncating variables. For a given nn …

Adaptive sampling schemes for density estimation

D Blanke - Journal of statistical planning and inference, 2006 - Elsevier
In this paper, first we propose sharp sampling schemes for nonparametric density estimation
for discretely observed continuous time processes. Next, since such samplings depend on …

The asymptotic variance of the continuous-time kernel estimator with applications to bandwidth selection

M Sköld - Statistical inference for stochastic processes, 2001 - Springer
We derive simple expressions for the asymptotic variance of the kernel-density estimator of a
stationary continuous-time process in one and d dimensions and relate convergence rates …

Iterative bias correction of the cross‐validation criterion

H Yanagihara, H Fujisawa - Scandinavian Journal of Statistics, 2012 - Wiley Online Library
The cross‐validation (CV) criterion is known to be asecond‐order unbiased estimator of the
risk function measuring the discrepancy between the candidate model and the true model …

Neural networks for bandwidth selection in local linear regression of time series

F Giordano, ML Parrella - Computational statistics & data analysis, 2008 - Elsevier
The problem of automatic bandwidth selection in nonparametric regression is considered
when a local linear estimator is used to derive nonparametrically the unknown regression …

[PDF][PDF] Kernel based methods for volatility modelling: the problem of bandwidth selection

F Giordano, ML Parrella - Conf. of the Italian Stat. Soc., Venice, 6 …, 2007 - sis-statistica.org
La volatilita dei rendimentie considerata una misura di rischio nei mercati finanziari. Sono
stati proposti in letteratura diversi e sofisticati modelli parametrici per l'analisi della volatilita …