Showing 6 of total 6 results (show query)
gavinsimpson
gratia:Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'
Graceful 'ggplot'-based graphics and utility functions for working with generalized additive models (GAMs) fitted using the 'mgcv' package. Provides a reimplementation of the plot() method for GAMs that 'mgcv' provides, as well as 'tidyverse' compatible representations of estimated smooths.
Maintained by Gavin L. Simpson. Last updated 10 hours ago.
distributional-regressiongamgammgeneralized-additive-mixed-modelsgeneralized-additive-modelsggplot2glmlmmgcvpenalized-splinerandom-effectssmoothingsplines
216 stars 12.95 score 1.6k scripts 2 dependents
mpascariu
ungroup:Penalized Composite Link Model for Efficient Estimation of Smooth Distributions from Coarsely Binned Data
Versatile method for ungrouping histograms (binned count data) assuming that counts are Poisson distributed and that the underlying sequence on a fine grid to be estimated is smooth. The method is based on the composite link model and estimation is achieved by maximizing a penalized likelihood. Smooth detailed sequences of counts and rates are so estimated from the binned counts. Ungrouping binned data can be desirable for many reasons: Bins can be too coarse to allow for accurate analysis; comparisons can be hindered when different grouping approaches are used in different histograms; and the last interval is often wide and open-ended and, thus, covers a lot of information in the tail area. Age-at-death distributions grouped in age classes and abridged life tables are examples of binned data. Because of modest assumptions, the approach is suitable for many demographic and epidemiological applications. For a detailed description of the method and applications see Rizzi et al. (2015) <doi:10.1093/aje/kwv020>.
Maintained by Marius D. Pascariu. Last updated 1 years ago.
distributionsglmsmoothingungroupingcpp
14 stars 5.96 score 65 scripts
arturstat
smoothHR:Smooth Hazard Ratio Curves Taking a Reference Value
Provides flexible hazard ratio curves allowing non-linear relationships between continuous predictors and survival. To better understand the effects that each continuous covariate has on the outcome, results are expressed in terms of hazard ratio curves, taking a specific covariate value as reference. Confidence bands for these curves are also derived.
Maintained by Artur Araujo. Last updated 1 years ago.
cox-modelgeneralized-additive-modelshazard-ratiossmoothingsurvival-analysis
2 stars 4.43 score 27 scripts
yukai-yang
SMFilter:Filtering Algorithms for the State Space Models on the Stiefel Manifold
Provides the filtering algorithms for the state space models on the Stiefel manifold as well as the corresponding sampling algorithms for uniform, vector Langevin-Bingham and matrix Langevin-Bingham distributions on the Stiefel manifold.
Maintained by Yukai Yang. Last updated 6 years ago.
filteringfiltering-algorithmnonlinear-dynamicsnonlinear-optimizationreduced-rank-parameterssamplingsimulated-datasmoothingstate-space-modelsstiefel-manifoldtime-series-models
2 stars 3.58 score 38 scripts
jrjthompson
nonsmooth:Nonparametric Methods for Smoothing Nonsmooth Data
Nonparametric methods for smoothing regression function data with change-points, utilizing range kernels for iterative and anisotropic smoothing methods. For further details, see the paper by John R.J. Thompson (2024) <doi:10.1080/02664763.2024.2352759>.
Maintained by John R.J. Thompson. Last updated 9 months ago.
change-pointchange-point-modelingchangepointkernelkernel-methodsnonparametric-regressionsmoothingsmoothing-methods
2.48 score
dfsp-spirit
haze:Smoothing of per-Vertex Data on Triangular Meshes
Smoothing of per-vertex data on triangular meshes, sub mesh creation based on vertex indices, per-vertex data interpolation based on k-d trees.
Maintained by Tim Schäfer. Last updated 2 years ago.
per-vertexsmoothingtriangular-meshcpp
5 stars 2.40 score