A nonparametric approach for estimating betas: the smoothed rolling estimator
نویسندگان
چکیده
منابع مشابه
A Berry-Esseen Type Bound for a Smoothed Version of Grenander Estimator
In various statistical model, such as density estimation and estimation of regression curves or hazard rates, monotonicity constraints can arise naturally. A frequently encountered problem in nonparametric statistics is to estimate a monotone density function f on a compact interval. A known estimator for density function of f under the restriction that f is decreasing, is Grenander estimator, ...
متن کاملBias Adjustment for a Nonparametric Entropy Estimator
Zhang in 2012 introduced a nonparametric estimator of Shannon’s entropy, whose bias decays exponentially fast when the alphabet is finite. We propose a methodology to estimate the bias of this estimator. We then use it to construct a new estimator of entropy. Simulation results suggest that this bias adjusted estimator has a significantly lower bias than many other commonly used estimators. We ...
متن کاملA Nonparametric Covariance Estimator for Spatial Models
The covariances in spatial models are estimated by linear smoothing of products of residuals. In the model no parametric assumptions are made about the mean function or the spatial dependence. Both are assumed to be smooth. Smoothing is based on local polynomials, though any linear smoother is possible to use. Expressions for the mean and the covariance of this estimator are developed and a ver...
متن کاملA Nonparametric Random Effects Estimator∗
This paper proposes feasible nonparametric random effects estimators. Specifically, we propose feasible versions of the two estimators in Lin and Carroll (2000) and a modified version of the random effects estimator in Ullah and Roy (1998). Further, the consistency properties of these estimators are established.
متن کاملA Smoothed Maximum Score Estimator for Multinomial Discrete Choice Models
We propose a semiparametric estimator for multinomial discrete choice models. The term “semiparametric” refers to the fact that we do not specify a particular functional form for the error term in the random utility function and we allow for heteroskedasticity and serial correlation. Despite being semiparametric, the rate of convergence of the smoothed maximum score estimator is not affected by...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Economics
سال: 2010
ISSN: 0003-6846,1466-4283
DOI: 10.1080/00036840701721257