Scan Science and Technology
Contact Leading Edge Experts & Companies
The Experts below are selected from a list of 10074 Experts worldwide ranked by ideXlab platform
Jinyong Hahn – 1st expert on this subject based on the ideXlab platform
Asymptotic Variance of semiparametric estimators with generated regressorsEconometrica, 2013Co-Authors: Jinyong Hahn, Geert RidderAbstract:
We study the Asymptotic distribution of three-step estimators of a finite-dimensional parameter vector where the second step consists of one or more nonparametric regressions on a regressor that is estimated in the first step. The first-step estimator is either parametric or nonparametric. Using Newey’s (1994) path-derivative method, we derive the contribution of the first-step estimator to the influence function. In this derivation, it is important to account for the dual role that the first-step estimator plays in the second-step nonparametric regression, that is, that of conditioning variable and that of argument.
a practical Asymptotic Variance estimator for two step semiparametric estimatorsThe Review of Economics and Statistics, 2011Co-Authors: Daniel A Ackerberg, Xiaohong Chen, Jinyong HahnAbstract:
The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric Variances using standard formulas derived in the already-well-known parametric literature. This means that for computational purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations “as if”it were a parametric situation. We hope that this simplicity will promote the use of semiparametric procedures.
Johan Lyhagen – 2nd expert on this subject based on the ideXlab platform
Asymptotic properties of spearman s rank correlation for variables with finite supportPLOS ONE, 2016Co-Authors: Petra Ornstein, Johan LyhagenAbstract:
The Asymptotic Variance and distribution of Spearman’s rank correlation have previously been known only under independence. For variables with finite support, the population version of Spearman’s rank correlation has been derived. Using this result, we show convergence to a normal distribution irrespectively of dependence, and derive the Asymptotic Variance. A small simulation study indicates that the Asymptotic properties are of practical importance.
Marvin K. Nakayama – 3rd expert on this subject based on the ideXlab platform
Confidence intervals for quantiles with standardized time series2013 Winter Simulations Conference (WSC), 2013Co-Authors: James M. Calvin, Marvin K. NakayamaAbstract:
Schruben (1983) developed standardized time series (STS) methods to construct confidence intervals (CIs) for the steady-state mean of a stationary process. STS techniques cancel out the Variance constant in the Asymptotic distribution of the centered and scaled estimator, thereby eliminating the need to consistently estimate the Asymptotic Variance to obtain a CI. This is desirable since estimating the Asymptotic Variance in steady-state simulations presents nontrivial challenges. Difficulties also arise in estimating the Asymptotic Variance of a quantile estimator. We show that STS methods can be used to build CIs for a quantile for the case of crude Monte Carlo (i.e., no Variance reduction) with independent and identically distributed outputs. We present numerical results comparing CIs for quantiles using STS to other procedures.