eshrink - Shrinkage for Effect Estimation

Computes shrinkage estimators for regression problems. Selects penalty parameter by minimizing bias and variance in the effect estimate, where bias and variance are estimated from the posterior predictive distribution. See Keller and Rice (2017) <doi:10.1093/aje/kwx225> for more details.

Last updated 5 years ago

2.70 score 1 stars 1 scripts 190 downloads

predkmeans - Covariate Adaptive Clustering

Implements the predictive k-means method for clustering observations, using a mixture of experts model to allow covariates to influence cluster centers. Motivated by air pollution epidemiology settings, where cluster membership needs to be predicted across space. Includes functions for predicting cluster membership using spatial splines and principal component analysis (PCA) scores using either multinomial logistic regression or support vector machines (SVMs). For method details see Keller et al. (2017) <doi:10.1214/16-AOAS992>.

Last updated 5 years ago

openblascpp

2.70 score 10 scripts 147 downloads

spconf - Computing Scales of Spatial Smoothing for Confounding Adjustment

Computes the effective range of a smoothing matrix, which is a measure of the distance to which smoothing occurs. This is motivated by the application of spatial splines for adjusting for unmeasured spatial confounding in regression models, but the calculation of effective range can be applied to smoothing matrices in other contexts. For algorithmic details, see Rainey and Keller (2024) "spconfShiny: an R Shiny application..." <doi:10.1371/journal.pone.0311440> and Keller and Szpiro (2020) "Selecting a Scale for Spatial Confounding Adjustment" <doi:10.1111/rssa.12556>.

Last updated 5 months ago

1.70 score 2 scripts 526 downloads