Some automated methods of smoothing time-dependent data

DOI10.1080/10485259608832667zbMath0878.62031OpenAlexW1964578728MaRDI QIDQ4345891

Jeffrey D. Hart

Publication date: 5 January 1998

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485259608832667

zbMATH Keywords

kernel estimatorscross-validationmean integrated squared errortransition densitiesautoregressionplug-in rulesprequential analysistime series cross-validationblockwise cross-validation

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Probabilistic methods, stochastic differential equations (65C99)

Related Items

Conditional time-dependent nonparametric estimators with an application to healthcare production function, A selective overview of nonparametric methods in financial econometrics, Plug-in bandwidth selector for local polynomial regression estimator with correlated errors, Assessing the performance of model-based clustering methods in multivariate time series with application to identifying regional wind regimes, Normalized least-squares estimation in time-varying ARCH models, Liquidity spreads in the corporate bondmarket: Estimation using a semi-parametric model, Smoothing parameter selection methods for nonparametric regression with spatially correlated errors, Competitive conditions and sectors' productive efficiency: a conditional non-parametric frontier analysis, REWEIGHTED FUNCTIONAL ESTIMATION OF DIFFUSION MODELS, NONPARAMETRIC INFERENCE FOR CONDITIONAL QUANTILES OF TIME SERIES, SMOOTHED BOOTSTRAP BANDWIDTH SELECTION IN NONPARAMETRIC DENSITY ESTIMATION FOR MOVING AVERAGE PROCESSES, Functional methods for time series prediction: a nonparametric approach, Nonparametric transfer function models, On a partly linear autoregressive model with moving average errors, Local linear regression for estimating time series data., MODEL-FREE INFERENCE FOR TAIL RISK MEASURES, Regression-type inference in nonparametric autoregression, Strong approximation of density estimators from weakly dependent observations by density estimators from independent observations, Neural networks for bandwidth selection in local linear regression of time series, Local linear extrapolation, Effect of dependence on stochastic measures of accuracy of density estimators, Robust kernel estimators for additive models with dependent observations, Variography for model selection in local polynomial regression with spatial data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Linear smoothers and additive models
• Kernel estimation for additive models under dependence
• Nonparametric regression with long-range dependence
• Nonparametric regression analysis of growth curves
• Density estimation for linear processes
• Convergence rates in density estimation for data from infinite-order moving average processes
• Data-driven bandwidth choice for density estimation based on dependent data
• Kernel estimation and interpolation for time series containing missing observations
• On smoothed probability density estimation for stationary processes
• An asymptotically optimal window selection rule for kernel density estimates
• Strong consistency and rates for recursive probability density estimators of stationary processes
• Bandwidth selection for kernel estimate with correlated noise
• Strong consistency of density estimation by orthogonal series methods for dependent variables with applications
• Comparison of two bandwidth selectors with dependent errors
• Nonparametric function estimation involving time series
• Testing goodness-of-fit in regression via order selection criteria
• Nonparametric estimation of Markov transition functions
• Nonparametric estimation of a regression function with dependent observations
• Growth curves: A two-stage nonparametric approach
• A data-based algorithm for choosing the window width when estimating the density at a point
• Consistency of cross-validation when the data are curves
• Nonparametric estimation in Markov processes
• [https://portal.mardi4nfdi.de/wiki/Publication:3038407 Propri�t�s de convergence presque compl�te du pr�dicteur � noyau]
• Analysis of Repeated Measurements Using Nonparametric Smoothers and Randomization Tests
• Selecting the Smoothing Parameter for Estimation of Slowly Changing Evoked Potential Signals
• NONPARAMETRIC ESTIMATORS FOR TIME SERIES
• Efficiency of a Kernel Density Estimator Under an Autoregressive Dependence Model
• On optimal data-based bandwidth selection in kernel density estimation
• The estimation of derivatives of a nonparametric regression function when the data are correlated
• The L/sub 1/ and L/sub 2/ strong consistency of recursive kernel density estimation from dependent samples
• Uniform Consistency of Kernel Estimators of a Regression Function Under Generalized Conditions
• Nonparametric Density Estimation, Prediction, and Regression for Markov Sequences
• Recursive probability density estimation for weakly dependent stationary processes
• Kernel Regression Estimation Using Repeated Measurements Data
• How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
• Biased and Unbiased Cross-Validation in Density Estimation
• Detecting Dependencies in Smooth Regression Models
• KERNEL REGRESSION SMOOTHING OF TIME SERIES
• Nonparametric spline regression with autoregressive moving average errors
• Design-adaptive Nonparametric Regression
• Kernel Regression When the Boundary Region is Large, With an Application to Testing the Adequacy of Polynomial Models
• Choice of bandwidth for kernel regression when residuals are correlated
• Convergence analysis of parametric identification methods
• Confidence Bands in Nonparametric Regression
• Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
• Bootstrap Test for Difference Between Means in Nonparametric Regression
• Kernel density estimation for linear processes