Showing 3 of total 3 results (show query)
sestelo
npregfast:Nonparametric Estimation of Regression Models with Factor-by-Curve Interactions
A method for obtaining nonparametric estimates of regression models with or without factor-by-curve interactions using local polynomial kernel smoothers or splines. Additionally, a parametric model (allometric model) can be estimated.
Maintained by Marta Sestelo. Last updated 2 months ago.
allometricbarnaclecritical-pointscurve-interactionsfactor-by-curvefortraninteractionnonparametricregression-modelstesting
14.5 match 5 stars 5.73 score 89 scripts 2 dependents
noramvillanueva
clustcurv:Determining Groups in Multiples Curves
A method for determining groups in multiple curves with an automatic selection of their number based on k-means or k-medians algorithms. The selection of the optimal number is provided by bootstrap methods. The methodology can be applied both in regression and survival framework. Implemented methods are: Grouping multiple survival curves described by Villanueva et al. (2018) <doi:10.1002/sim.8016>.
Maintained by Nora M. Villanueva. Last updated 4 months ago.
clusteringdata-analyticsmachinelearningmultiple-curvesnonparametric-statisticsnumber-of-clustersregressionsurvival-analysis
4.5 match 3 stars 5.53 score 38 scripts
cran
PLRModels:Statistical Inference in Partial Linear Regression Models
Contains statistical inference tools applied to Partial Linear Regression (PLR) models. Specifically, point estimation, confidence intervals estimation, bandwidth selection, goodness-of-fit tests and analysis of covariance are considered. Kernel-based methods, combined with ordinary least squares estimation, are used and time series errors are allowed. In addition, these techniques are also implemented for both parametric (linear) and nonparametric regression models.
Maintained by Ana Lopez-Cheda. Last updated 2 years ago.
8.0 match 1.00 score