Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
From MaRDI portal
Publication:4214237
DOI10.1111/1467-9868.00125zbMath0909.62039OpenAlexW2109785413MaRDI QIDQ4214237
Clifford M. Hurvich, Jeffrey S. Simonoff
Publication date: 8 April 1999
Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/1467-9868.00125
plug-in methodconvolution kernel regression estimatorlocal polynomial regression estimatorsmoothing spline regression estimator
Related Items
Greedy algorithms for prediction, Nonparametric estimation of simplified vine copula models: comparison of methods, Tuning parameter selection in sparse regression modeling, Selection of smoothing parameters in \(B\)-spline nonparametric regression models using information criteria, Plasmode simulation for the evaluation of pharmacoepidemiologic methods in complex healthcare databases, Kernel estimation of hazard functions when observations have dependent and common covariates, A generalized correlated \(C_p\) criterion for derivative estimation with dependent errors, A new algorithm for fitting semi-parametric variance regression models, Fiscal policy and asset markets: a semiparametric analysis, Functional-coefficient models for nonstationary time series data, Boosting techniques for nonlinear time series models, Wavelet-based gradient boosting, From local kernel to nonlocal multiple-model image denoising, An empirical comparison of classification algorithms for mortgage default prediction: evidence from a distressed mortgage market, From finite sample to asymptotics: a geometric bridge for selection criteria in spline regression, Partially linear models with first-order autoregressive symmetric errors, Nonparametric models and their estimation, Pointwise convergence in probability of general smoothing splines, Growth volatility and size: a firm-level study, The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation, On discrete Epanechnikov kernel functions, A geometrical approach to iterative isotone regression, Estimating and interpreting effects from nonlinear exposure-response curves in occupational cohorts using truncated power basis expansions and penalized splines, Augmented factor models with applications to validating market risk factors and forecasting bond risk premia, Additive nonparametric instrumental regressions: a guide to implementation, Using local learning with fuzzy transform: application to short term forecasting problems, Genetic algorithms for the selection of smoothing parameters in additive models, Environmental regulation and US state-level production, Mixtures of regressions with changepoints, Calculating degrees of freedom in multivariate local polynomial regression, Nonparametric inference for additive models estimated via simplified smooth backfitting, Reference optimality criterion for planning accelerated life testing, An exponential-type kernel robust regression model for interval-valued variables, A comparative study of nonparametric estimation in Weibull regression: a penalized likelihood approach, Semiparametric additive models under symmetric distributions, Functional regression modeling via regularized Gaussian basis expansions, Contrast-based information criterion for ergodic diffusion processes from discrete observations, Penalized regression with individual deviance effects, Functional principal component analysis of spatially correlated data, Simplicity and model selection, Local bandwidth selection via second derivative segmentation, Penalized wavelets: embedding wavelets into semiparametric regression, The use of geographically weighted regression for the relationship among extreme climate indices in China, Boosting algorithms: regularization, prediction and model fitting, Local linear hazard rate estimation and bandwidth selection, Generalized additive models and inflated type I error rates of smoother significance tests, Is \(C_{p}\) an empirical Bayes method for smoothing parameter choice?, Effective degrees of freedom and its application to conditional AIC for linear mixed-effects models with correlated error structures, Early stopping in \(L_{2}\)Boosting, Enhancement of spatially adaptive smoothing splines via parameterization of smoothing parameters, Comparative analysis for robust penalized spline smoothing methods, Selection of tuning parameters in bridge regression models via Bayesian information criterion, Boosting iterative stochastic ensemble method for nonlinear calibration of subsurface flow models, Omnibus test for covariate effects in conditional copula models, Effect of autocorrelation when estimating the trend of a time series via penalized least squares with controlled smoothness, Explaining individual predictions when features are dependent: more accurate approximations to Shapley values, Constrained regression model selection, Subspace Information Criterion for Model Selection, Response shrinkage estimators in binary regression, Boosting additive models using component-wise P-splines, Shrinkage and model selection with correlated variables via weighted fusion, Comparing measures of model selection for penalized splines in Cox models, Local adaptive smoothing in kernel regression estimation, An unbiased \(C_p\) criterion for multivariate ridge regression, SmoothHR: an R package for pointwise nonparametric estimation of hazard ratio curves of continuous predictors, Estimating the expectation of the Log-likelihood with censored data for estimator selection, Improved smoothing spline regression by combining estimates of different smoothness, Nonparametric regression under alternative data environments, An improved \(C_p\) criterion for spline smoothing, Boosting for high-dimensional linear models, An \(R\)-square coefficient based on final prediction error, Easy recipes for cooperative smoothing, On nonparametric comparison of images and regression surfaces, Kernel smoothers: an overview of curve estimators for the first graduate course in nonparametric statistics, Nonparametric \(F\)-tests for nested global and local polynomial models, Feature screening for multi-response varying coefficient models with ultrahigh dimensional predictors, Corrected Mallows criterion for model averaging, Semiparametric mixtures of nonparametric regressions, A non-iterative optimization method for smoothness in penalized spline regression, Iterative bias reduction: a comparative study, Spatial econometric approach to the EU regional employment process, Functional principal component analysis via regularized Gaussian basis expansions and its application to unbalanced data, Parsimonious additive models, Parametric and semi-parametric approaches in the analysis of short-term effects of air pollution on health, Knot selection by boosting techniques, Empirical foundation of valence using Aldrich-McKelvey scaling, Stacked Laplace-EM algorithm for duration models with time-varying and random effects, Improved AIC selection strategy for survival analysis, Simultaneous selection of variables and smoothing parameters in structured additive regression models, A fast algorithm for optimizing ridge parameters in a generalized ridge regression by minimizing a model selection criterion, Optimal model averaging for multivariate regression models, Nonparametric Bayesian estimation of a Hölder continuous diffusion coefficient, Boosting as a kernel-based method, Nonparametric regression penalizing deviations from additivity, Semiparametric regression model selections., Testing heteroscedasticity in nonparametric regression based on trend analysis, Semi-nonparametric estimation of the call-option price surface under strike and time-to-expiry no-arbitrage constraints, Time-varying nonlinear regression models: nonparametric estimation and model selection, A comparative review of dimension reduction methods in approximate Bayesian computation, Quantile regression using RJMCMC algorithm, Optimal model averaging estimator for multinomial logit models, Unnamed Item, Penalized Partial Likelihood for Frailties and Smoothing Splines in Time to First Insemination Models for Dairy Cows, Optimum smoothing parameter selection for penalized least squares in form of linear mixed effect models, Bridging the Gap BetweenB-Spline and Polynomial Regression Model, A critical review of univariate non-parametric estimation of first derivatives, Automatic Smoothing and Estimation in Single Index Poisson Regression, Local linear variable bandwidth hazard rate estimation, Iterative Bias Correction of the Cross-Validation Criterion, Optimum shrinkage parameter selection for ridge type estimator of Tobit model, Additive Functional Cox Model, Evaluation of some random effects methodology applicable to bird ringing data, Residual information criterion for single-index model selections, Semiparametric modelling of multicategorical data, Schwarz, Wallace, and Rissanen: Intertwining Themes in Theories of Model Selection, Truncation level selection in nonparametric regression using Padé approximation, Robust mixture regression modeling based on the generalized M (GM)-estimation method, Using pseudometrics in kernel density estimation, Clustering High-Dimensional Time Series Based on Parallelism, Modified spline regression based on randomly right-censored data: A comparative study, A model-averaging approach for smoothing spline regression, Statistical inference using regularized M-estimation in the reproducing kernel Hilbert space for handling missing data, On the selection of predictors by using greedy algorithms and information theoretic criteria, Predictors with measurement error in mixtures of polynomial regressions, Continuous-time state-space modelling of the hot hand in basketball, Validation and comparison of geostatistical and spline models for spatial stream networks, Empirical likelihood inference for monotone index model, Minorize–maximize algorithm for the generalized odds rate model for clustered current status data, Tuning parameter selection for nonparametric derivative estimation in random design, High-dimensional local linear regression under sparsity and convex losses, Trend smoothness achieved by penalized least squares with the smoothing parameter chosen by optimality criteria, Semiparametric analysis for case-control studies: a partial smoothing spline approach, Model selection in regression based on pre-smoothing, Unnamed Item, A Markov-switching generalized additive model for compound Poisson processes, with applications to operational loss models, Kernel spline regression, A Comparison of Two Bandwidth Selectors OSCV and AICc in Nonparametric Regression, Local influence for elliptical partially varying-coefficient model, A generalized additive model approach to time-to-event analysis, Improved local quantile regression, KyPlot as a Tool for Graphical Data Analysis, Functional Generalized Linear Models with Images as Predictors, Selecting the Number of Principal Components in Functional Data, The conditional breakdown properties of least absolute value local polynomial estimators, Monotone Nonparametric Regression and Confidence Intervals, Prediction of Stock Returns: A New Way to Look at It, Regression Model Selection—A Residual Likelihood Approach, A COMPARISON OF MIXED MODEL SPLINES FOR CURVE FITTING, MODEL SELECTION FOR PENALIZED SPLINE SMOOTHING USING AKAIKE INFORMATION CRITERIA, Smoothing and forecasting mortality rates, Selection Strategy for Covariance Structure of Random Effects in Linear Mixed-effects Models, A GRAPHICAL DIAGNOSTIC FOR VARIANCE FUNCTIONS, Smoothing a Time Series by Segments of the Data Range, Model averaging quantiles from data censored by a limit of detection, KERNEL DENSITY ESTIMATION WITH MISSING DATA AND AUXILIARY VARIABLES, Selecting the amount of smoothing in nonparametric regression estimation for complex surveys, Bootstrap Choice of Estimators in Parametric and Semiparametric Families: An Extension of EIC, Generalized Semiparametrically Structured Ordinal Models, Non‐parametric Quantile Regression with Censored Data, Flexible hazard ratio curves for continuous predictors in multi-state models, Building Cox-type structured hazard regression models with time-varying effects, Using the Box-Cox t distribution in GAMLSS to model skewness and kurtosis, Comparing nonparametric surfaces, Cox regression models with functional covariates for survival data, A new information criterion-based bandwidth selection method for non-parametric regressions, A Comparative Study of Semiparametric Estimation in Partially Linear Single-index Models, Understanding past ocean circulations: a nonparametric regression case study, Non parametric hypothesis tests for comparing reliability functions, Finite Sample Performances of the Model Selection Approach in Nonparametric Model Specification for Time Series, Computational aspects in local image denoising and reconstruction with correlated errors, WaverideR, Local quasi-likelihood approach to varying-coefficient discrete-valued time series models, Distributed Lag Models for Hydrological Data, Smoothing parameter selection in quasi-likelihood models, Flexible smoothing with P-splines: a unified approach, Three Sides of Smoothing: Categorical Data Smoothing, Nonparametric Regression, and Density Estimation, Nonparametric estimation of marginal effects in regression-spline random effects models, An Efficient Operator for the Change Point Estimation in Partial Spline Model, Semiparametric transition models, Univariate measurement error selection likelihood for variable selection of additive model, Comment on: ``Local quantile regression, Forecasting Inflation Rates Using Daily Data: A Nonparametric MIDAS Approach
