Related papers: Toward Variation-Independent Regression by Composi…

Discussion on ``Regression by Composition'' by Farewell, Daniel, Stensrud, and Huitfeldt

We discuss the regression-by-composition framework of Farewell, Daniel, Stensrud and Huitfeldt, highlighting a key consequence of its sequential construction: order dependence. Reordering the flows may change the implied conditional…

Compositional data are common in many fields, both as outcomes and predictor variables. The inventory of models for the case when both the outcome and predictor variables are compositional is limited and the existing models are difficult to…

Distance covariance and distance correlation have long been regarded as natural measures of dependence between two random vectors, and have been used in a variety of situations for testing independence. Despite their popularity, the…

Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]

Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]

Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]

Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]

Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]

Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]

Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]

Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]

In compositional data, an observation is a vector with non-negative components which sum to a constant, typically 1. Data of this type arise in many areas, such as geology, archaeology, biology, economics and political science amongst…

This note provides additional interpretation for the counterfactual outcome distribution and corresponding unconditional quantile "effects" defined and estimated by Firpo, Fortin, and Lemieux (2009) and Chernozhukov, Fern\'andez-Val, and…

This paper studies the case of possibly high-dimensional covariates in the regression discontinuity design (RDD) analysis. In particular, we propose estimation and inference methods for the RDD models with covariate selection which perform…

Rejoinder to ``Least angle regression'' by Efron et al. [math.ST/0406456]

In this paper, we consider a regression model built on dependent variables. This regression modelizes an input output relationship. Under boundedness assumptions on the joint distribution function of the input variables, we show that a…

Shape restricted regressions, including isotonic regression and concave regression as special cases, are studied using priors on Bernstein polynomials and Markov chain Monte Carlo methods. These priors have large supports, select only…

This is the rejoinder for discussion of "Multinomial Inverse Regression for Text Analysis", Journal of the American Statistical Association 108, 2013.

We provide a remedy for two concerns that have dogged the use of principal components in regression: (i) principal components are computed from the predictors alone and do not make apparent use of the response, and (ii) principal components…