Results 71 to 80 of about 73,585 (174)
Much empirical research is concerned with estimating conditional mean, median, or hazard functions. For example, labor economists are interested in estimating the mean wages of employed individuals conditional on characteristics such as years of work ...
Horowitz, Joel L.
core
Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms [PDF]
arXiv, 2019 Nonparametric series regression often involves specification search over the tuning parameter, i.e., evaluating estimates and confidence intervals with a different number of series terms. This paper develops pointwise and uniform inferences for conditional mean functions in nonparametric series estimations that are uniform in the number of series terms.
arxiv
A likelihood ratio test for monotone baseline hazard functions in the Cox model [PDF]
arXiv, 2013 We consider a likelihood ratio method for testing whether a monotone baseline hazard function in the Cox model has a particular value at a fixed point. The characterization of the estimators involved is provided both in the nondecreasing and the nonincreasing setting.
arxiv
Using Expectations Data to Study Subjective Income Expectations [PDF]
We have collected data on the one-year-ahead income expectations of members of American households in our Survey of Economic Expectations (SEE), a module of a national continuous telephone survey conducted at the University of Wisconsin.
Charles F. Manski, Jeff Dominitz
core +3 more sources
Nonparametric Risk Assessment and Density Estimation for Persistence Landscapes [PDF]
arXiv, 2018 This paper presents approximate confidence intervals for each function of parameters in a Banach space based on a bootstrap algorithm. We apply kernel density approach to estimate the persistence landscape. In addition, we evaluate the quality distribution function estimator of random variables using integrated mean square error (IMSE).
arxiv
, 2017 The precision of an estimator is at times discussed regarding the variance. Usually, the exact value of the variance is unknown. The discussion relies on unknown populace quantities.
Nicholas Makumi +3 more
semanticscholar +1 more source
Productivity Dynamics and Structural Change in the U.S. Manufacturing Sector [PDF]
The paper investigates structural change among the four-digit (SIC) industries of the U.S. manufacturing sector during 1958-96 within a distribution dynamics framework. Focus is on the transition density of the Markov process that characterizes the value
Jens J. Krüger
core
, 2019 We consider a nonparametric instrumental regression model with continuous endogenous regressor where instruments are fully independent of the error term. This assumption allows us to extend the reach of this model to cases where the instrumental variable
Centorrino, Samuele +2 more
core
Frequentist size of Bayesian inequality tests
, 2018 Bayesian and frequentist criteria are fundamentally different, but often posterior and sampling distributions are asymptotically equivalent (e.g., Gaussian).
Kaplan, David M., Zhuo, Longhao
core
Nonparametric Conditional Inference for Regression Coefficients with Application to Configural Polysampling [PDF]
arXiv, 2007 We consider inference procedures, conditional on an observed ancillary statistic, for regression coefficients under a linear regression setup where the unknown error distribution is specified nonparametrically. We establish conditional asymptotic normality of the regression coefficient estimators under regularity conditions, and formally justify the ...
arxiv