Kernel Function in Local Linear Peters-Belson Regression
نویسندگان
چکیده
منابع مشابه
The Use of Peters-Belson Regression in Legal Cases
In equal employment cases it is important to compare the salary, hiring or promotion status of minority employees or applicants to that of similarly qualified majority members. Standard regression methods include a binary variable indicating minority status along with major job-related variables to assess whether belonging to a minority has a negative effect. Implicitly, this method assumes tha...
متن کاملImproved double kernel local linear quantile regression
As sample quantiles can be obtained as maximum likelihood estimates of location parameters in suitable asymmetric Laplace distributions, so kernel estimates of quantiles can be obtained as maximum likelihood estimates of location parameters in a general class of distributions with simple exponential tails. In this paper, this observation is applied to kernel quantile regression. In so doing, a ...
متن کاملOptimal Kernel Shapes for Local Linear Regression
Local linear regression performs very well in many low-dimensional forecasting problems. In high-dimensional spaces, its performance typically decays due to the well-known "curse-of-dimensionality". A possible way to approach this problem is by varying the "shape" of the weighting kernel. In this work we suggest a new, data-driven method to estimating the optimal kernel shape. Experiments using...
متن کاملLocal Linear Smoothers in Regression Function Estimation
A method based on local linear approximation is used to estimate the mean regression function. The proposed local linear smoother has several advantages in comparison with other linear smoothers. Motivated by this fact, we follow this approach to estimate more general functions, among which, conditional median and conditional quantile functions. A further generalization involves the estimation ...
متن کاملLeaving Local Optima in Unsupervised Kernel Regression
Abstract. Embedding high-dimensional patterns in low-dimensional latent spaces is a challenging task. In this paper, we introduce re-sampling strategies to leave local optima in the data space reconstruction error (DSRE) minimization process of unsupervised kernel regression (UKR). For this sake, we concentrate on a hybrid UKR variant that combines iterative solution construction with gradient ...
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: Revista Colombiana de Estadística
سال: 2018
ISSN: 2389-8976,0120-1751
DOI: 10.15446/rce.v41n2.65654