
BartPy
 Referenced in 83 articles
[sw40584]
 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...

BayesTree
 Referenced in 64 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 15 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 hardtojustify, but commonly made, statistical...

TwoCop
 Referenced in 59 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...

npsp
 Referenced in 4 articles
[sw31433]
 regression, density and variogram estimation. Nonparametric methods for simultaneous inference on both spatial trend...

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 searchlightbased...

BayClone2
 Referenced in 1 article
[sw31387]
 characterize tumor heterogeneity using Bayesian nonparametric inference. Specifically, we estimate the number of subclones...

beyondWhittle
 Referenced in 8 articles
[sw31734]
 Bayesian Spectral Inference for Stationary Time Series. Implementations of Bayesian parametric, nonparametric and semiparametric procedures...

lspartition
 Referenced in 2 articles
[sw30834]
 package lspartition: Nonparametric Estimation and Inference Procedures using PartitioningBased Least Squares Regression. Tools ... Cattaneo, Farrell and Feng (2019b, ): lsprobust() for nonparametric point estimation of regression functions and their ... robust biascorrected (pointwise and uniform) inference; lspkselect() for datadriven selection of the IMSE...

ATE
 Referenced in 2 articles
[sw35701]
 Treatment Effects using Covariate Balancing. Nonparametric estimation and inference for average treatment effects based...

nprobust
 Referenced in 3 articles
[sw30833]
 package nprobust: Nonparametric Robust Estimation and Inference Methods using Local Polynomial Regression and Kernel Density...

drtmle
 Referenced in 2 articles
[sw37282]
 package drtmle: DoublyRobust Nonparametric Estimation and Inference. Targeted minimum lossbased estimators of counterfactual...

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 timeseries 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...

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...

ROCKET
 Referenced in 13 articles
[sw30016]
 setting. In this paper, we focus on inference for edge parameters in a highdimensional ... 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 11 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...

npsf
 Referenced in 2 articles
[sw35585]
 Efficiency and Productivity Analysis. Nonparametric efficiency measurement and statistical inference via DEA type estimators...

dirichletprocess
 Referenced in 4 articles
[sw32614]
 Perform nonparametric Bayesian analysis using Dirichlet processes without the need to program the inference algorithms...

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