- Referenced in 317 articles
- Smoothing spline ANOVA models Nonparametric function estimation with stochastic data, otherwise known as smoothing...
- Referenced in 143 articles
- plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection...
- Referenced in 53 articles
- maximum likelihood estimator (MLE) of a density as well as a smoothed version ... Duembgen and Rufibach (2009). The main function of the package is ’logConDens’ that allows computation ... concave MLE and its smoothed version. In addition, we provide functions to compute ... density and distribution function estimates (MLE and smoothed) at a given point (2) the characterizing...
- Referenced in 459 articles
- mixture of both. The nonlinear functions must be smooth. Stable numerical methods are employed throughout ... automatic scaling of linear contraints, and automatic estimation of some or all gradients. Upper...
- Referenced in 107 articles
- smoothness estimation. Routines for GAMs and other generalized ridge regression with multiple smoothing parameter selection ... UBRE/AIC. Also GAMMs. Includes a gam() function...
- Referenced in 14 articles
- package for producing a smooth estimate of the hazard function for censored data...
- Referenced in 67 articles
- contains R-functions to perform the methods in nonparametric regression and density estimation, described ... p1093-1136 Kovac, A. (2006) Smooth functions and local extreme values. Computational Statistics and Data...
- Referenced in 48 articles
- package contains R-functions implementing the Propagation-Separation Approach to adaptive smoothing as described ... Propagation-Separation Approach for Local Likelihood Estimation, Prob. Theory and Rel. Fields...
- Referenced in 9 articles
- Differential Equations. This package provides functions for estimation of linear and non-linear mixed-effects ... differential equations. Moreover it provides functions for finding smoothed estimates of model states...
- Referenced in 7 articles
- Recursive bias estimation for multivariate regression smoothers. This paper presents a practical and simple fully ... underlying smoothness of the true regression function. Our estimator is easily computed by successive application ... without the need of selecting an optimal smoothing parameter), such as thin-plate spline...
- Referenced in 11 articles
- simest: Constrained Single Index Model Estimation. Estimation of function and index vector in single index ... with and without shape constraints including different smoothness conditions...
- Referenced in 70 articles
- first-order iterative “shrinkage” method yields an estimate of the subset of components ... norm ∥x∥ 1 to a linear function of x. The resulting subspace problem, which involves ... minimization of a smaller and smooth quadratic function, is solved in the second phase...
Signal Processing Toolbox
- Referenced in 25 articles
- Signal Processing Toolbox. Signal Processing Toolbox™ provides functions and apps to generate, measure, transform, filter ... algorithms for resampling, smoothing, and synchronizing signals, designing and analyzing filters, estimating power spectra...
- Referenced in 4 articles
- Spatiotemporal Relative Risk. Provides functions to estimate kernel-smoothed spatial and spatio-temporal densities...
- Referenced in 5 articles
- functions to implement the Hillmer-Tiao canonical decomposition and the smooth trend and cycle estimation ... other functions can be used for likelihood evaluation, model estimation, forecasting and smoothing ... manual to illustrate the use of these functions...
- Referenced in 2 articles
- Bayesian hierarchical model for smoothing functional data and estimating mean-covariance functions simultaneously and nonparametricaly ... functional data. Examples of functional data regression with one functional independent variable, scalar and functional ... BFDA include: (1) Simultaneously smooths functional data and estimates the mean-covariance functions ... both stationary and nonstationary functional data; (4) Provides accurately smoothed functional data for follow...
- Referenced in 6 articles
- state space models). Includes functions for Kalman filtering and smoothing. Estimation of variance matrices...
- Referenced in 3 articles
- variable selection and smoothing for high-dimensional function-on-scalar regression. We present ... selects important predictors and produces smooth estimates in a function-on-scalar linear model with ... select important predictors while also producing smooth parameter estimates, we utilize operators to define subspaces ... algorithm for computing the estimators, which is based on a functional coordinate descent...
- Referenced in 44 articles
- estimation on the hazard function but also a parametric estimation. 1) A shared gamma frailty ... recurrent events). An automatic choice of the smoothing parameter is possible using an approximated cross...
- Referenced in 4 articles
- Disake: Discrete associated kernel estimators. Discrete smoothing of probability mass function is performed using three...