Asymptotic Distribution of Least Squares Estimators for Purely Unstable Arma (m,∞)

Statistics ◽  
1996 ◽  
Vol 28 (4) ◽  
pp. 307-346 ◽  
Author(s):  
B. Truong-Van ◽  
I. Larramendy
Keyword(s):  
Least Squares ◽  
Asymptotic Distribution ◽  
Least Squares Estimators

Least Squares Regression with Integrated or Dynamic Regressors under Weak Error Assumptions

1987 ◽  
Vol 3 (1) ◽  
pp. 98-116 ◽  
Author(s):  
Donald W. K. Andrews
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Least Squares ◽  
Asymptotic Distribution ◽  
Linear Regression Model ◽  
Multiple Regression Model ◽  
Least Squares Regression ◽  
Least Squares Estimators ◽  
Integrated Or ◽  
Weak Error

This paper establishes consistency of least squares estimators in (i) a multiple regression model with integrated regressors and explosive, non-mixing errors, and (ii) a dynamic linear regression model with regressors and errors that may have infinite variances. In the former context, the asymptotic distribution of the least squares estimator also is obtained, in certain cases.

On the Asymptotic Distribution of the Least-Squares Estimators in Unidentifiable Models

2004 ◽  
Vol 16 (1) ◽  
pp. 99-114 ◽  
Author(s):  
Taichi Hayasaka ◽  
Masashi Kitahara ◽  
Shiro Usui
Keyword(s):  
Asymptotic Normality ◽  
Least Squares ◽  
Asymptotic Distribution ◽  
Linear Models ◽  
Stochastic Property ◽  
Learning Machines ◽  
Least Squares Estimators

In order to analyze the stochastic property of multilayered perceptrons or other learning machines, we deal with simpler models and derive the asymptotic distribution of the least-squares estimators of their parameters. In the case where a model is unidentified, we show different results from traditional linear models: the well-known property of asymptotic normality never holds for the estimates of redundant parameters.

scholarly journals A New Inverted Topp-Leone Distribution: Applications to the COVID-19 Mortality Rate in Two Different Countries

Axioms ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 25 ◽  
Author(s):  
Ehab Almetwally ◽  
Randa Alharbi ◽  
Dalia Alnagar ◽  
Eslam Hafez
Keyword(s):  
Statistical Model ◽  
Least Squares ◽  
Weighted Least Squares ◽  
Likelihood Estimation ◽  
Linear Representation ◽  
Rate Function ◽  
Estimation Methods ◽  
Unknown Parameters ◽  
Least Squares Estimators ◽  
New Distribution

This paper aims to find a statistical model for the COVID-19 spread in the United Kingdom and Canada. We used an efficient and superior model for fitting the COVID 19 mortality rates in these countries by specifying an optimal statistical model. A new lifetime distribution with two-parameter is introduced by a combination of inverted Topp-Leone distribution and modified Kies family to produce the modified Kies inverted Topp-Leone (MKITL) distribution, which covers a lot of application that both the traditional inverted Topp-Leone and the modified Kies provide poor fitting for them. This new distribution has many valuable properties as simple linear representation, hazard rate function, and moment function. We made several methods of estimations as maximum likelihood estimation, least squares estimators, weighted least-squares estimators, maximum product spacing, Crame´r-von Mises estimators, and Anderson-Darling estimators methods are applied to estimate the unknown parameters of MKITL distribution. A numerical result of the Monte Carlo simulation is obtained to assess the use of estimation methods. also, we applied different data sets to the new distribution to assess its performance in modeling data.

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