A New Method For Point Estimating Parameters Of Simple Regression
A new method is described for finding parameters of univariate regression model: the greatest cosine method. Implementation of the method involves division of regression model parameters into two groups. The first group of parameters responsible for the angle between the experimental data vector and...
Main Authors: | Boris Nikolaevich Kazakov, Andrei Vyacheslavovich Mikheev |
---|---|
Format: | Article |
Language: | Russian |
Published: |
Institute of Computer Science
2014-02-01
|
Series: | Компьютерные исследования и моделирование |
Subjects: | |
Online Access: | http://crm.ics.org.ru/uploads/crmissues/crm_2014_1/14105.pdf |
Similar Items
-
Bloch-Gruneisen Fonksiyonu ile Bazı Katıların Elektriksel Özdirencinin Sıcaklığa Göre Değişiminin Analitik İncelenmesi
by: Mustafa Karakaya, et al.
Published: (2013-06-01) -
Bootstrapping Residuals to Estimate the Standard Error of Simple Linear Regression Coefficients
by: Muhammad Hasan Sidiq Kurniawan
Published: (2016-06-01) -
Kernel Partial Least Square Regression with High Resistance to Multiple Outliers and Bad Leverage Points on Near-Infrared Spectral Data Analysis
by: Divo Dharma Silalahi, et al.
Published: (2021-03-01) -
Gateaux Differentiable Points of Simple Type
by: Oh, Seung Jae
Published: (1982) -
Identification of Influential Points in a Linear Regression Model
by: Jan Grosz
Published: (2011-03-01)