• BayesTree

  • Referenced in 59 articles [sw07995]
  • weak learner, and fitting and inference are accomplished via an iterative Bayesian backfitting MCMC algorithm ... from a posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive ... likelihood. This approach enables full posterior inference including point and interval estimates of the unknown...
  • MatchIt

  • Referenced in 13 articles [sw10538]
  • MatchIt: Nonparametric Preprocessing for Parametric Causal Inference. MatchIt implements the suggestions of Ho, Imai, King ... parametric statistical models by preprocessing data with nonparametric matching methods. MatchIt implements a wide range ... greatly reduce the dependence of causal inferences on hard-to-justify, but commonly made, statistical...
  • TwoCop

  • Referenced in 52 articles [sw12359]
  • between two copulas. This package implements the nonparametric test of equality between two copulas proposed ... structures estimated through empirical copulas. We provide inference for independent or paired samples. The multiplier...
  • rsatoolbox

  • Referenced in 1 article [sw32148]
  • neuronal recording techniques. Tools for visualization and inference enable the user to relate sets ... test and compare the models using nonparametric inference methods. The toolbox supports searchlight-based...
  • BayClone2

  • Referenced in 1 article [sw31387]
  • characterize tumor heterogeneity using Bayesian nonparametric inference. Specifically, we estimate the number of subclones...
  • npsp

  • Referenced in 3 articles [sw31433]
  • regression, density and variogram estimation. Nonparametric methods for simultaneous inference on both spatial trend...
  • lspartition

  • Referenced in 2 articles [sw30834]
  • package lspartition: Nonparametric Estimation and Inference Procedures using Partitioning-Based Least Squares Regression. Tools ... Cattaneo, Farrell and Feng (2019b, ): lsprobust() for nonparametric point estimation of regression functions and their ... robust bias-corrected (pointwise and uniform) inference; lspkselect() for data-driven selection of the IMSE...
  • beyondWhittle

  • Referenced in 6 articles [sw31734]
  • Bayesian Spectral Inference for Stationary Time Series. Implementations of Bayesian parametric, nonparametric and semiparametric procedures...
  • TDAstats

  • Referenced in 1 article [sw31276]
  • calculations; (3) visualizing persistent homology and statistical inference. The published form of TDAstats ... permutation test is used for nonparametric statistical inference in topological data analysis, read Robinson & Turner...
  • tssreg

  • Referenced in 0 articles [sw37605]
  • Uniform nonparametric inference for time series using Stata. In this article, we introduce a command ... tssreg, that conducts nonparametric series estimation and uniform inference for time-series data, including ... case. This command can be used to nonparametrically estimate the conditional expectation function ... dependence. The uniform inference tool can also be used to perform nonparametric specification tests...
  • ATE

  • Referenced in 1 article [sw35701]
  • Treatment Effects using Covariate Balancing. Nonparametric estimation and inference for average treatment effects based...
  • nprobust

  • Referenced in 2 articles [sw30833]
  • package nprobust: Nonparametric Robust Estimation and Inference Methods using Local Polynomial Regression and Kernel Density...
  • npregfast

  • Referenced in 1 article [sw23053]
  • npregfast: An R Package for Nonparametric Estimation and Inference in Life Sciences. We present ... study of living organisms. The package implements nonparametric estimation procedures in regression models with ... package is its ability to perform inference regarding these models. Namely, the implementation of different...
  • drtmle

  • Referenced in 1 article [sw37282]
  • package drtmle: Doubly-Robust Nonparametric Estimation and Inference. Targeted minimum loss-based estimators of counterfactual...
  • ROCKET

  • Referenced in 11 articles [sw30016]
  • setting. In this paper, we focus on inference for edge parameters in a high-dimensional ... sparse spectral norm of the nonparametric Kendall’s tau estimator of the correlation matrix, which ... Gaussian models in terms of achieving accurate inference on simulated data. We also compare...
  • DepthProc

  • Referenced in 8 articles [sw17738]
  • user friendly tools for robust exploration and inference for multivariate data. The offered techniques ... parametric models generating data due to their nonparametric nature. The package consist of among others...
  • CSI

  • Referenced in 1 article [sw13904]
  • nonparametric Bayesian approach to network inference from multiple perturbed time series gene expression data. Here...
  • npsf

  • Referenced in 1 article [sw35585]
  • Efficiency and Productivity Analysis. Nonparametric efficiency measurement and statistical inference via DEA type estimators...
  • dirichletprocess

  • Referenced in 3 articles [sw32614]
  • Perform nonparametric Bayesian analysis using Dirichlet processes without the need to program the inference algorithms...
  • phylodyn

  • Referenced in 3 articles [sw19813]
  • package for phylodynamic simulation and inference. We introduce phylodyn, an R package for phylodynamic analysis ... genealogies. The package main functionality is Bayesian nonparametric estimation of effective population size fluctuations over ... nested Laplace approximation-based approach for phylodynamic inference that have been developed in recent years...