scholarly journals Estimation of Parameters of Network Equilibrium Models: A Maximum Likelihood Method and Statistical Properties of Network Flow

2009 ◽  
pp. 39-56 ◽  
Author(s):  
Shoichiro Nakayama ◽  
Richard D.
Keyword(s):  
Maximum Likelihood ◽  
Network Flow ◽  
Maximum Likelihood Method ◽  
Statistical Properties ◽  
Likelihood Method ◽  
Network Equilibrium ◽  
Estimation Of Parameters ◽  
Equilibrium Models

scholarly journals A New One-parameter G Family of Compound Distributions: Copulas, Statistical Properties and Applications

2021 ◽  
Vol 9 (4) ◽  
pp. 942-962
Author(s):  
Mohamed Abo Raya
Keyword(s):  
Maximum Likelihood ◽  
Hazard Function ◽  
Maximum Likelihood Method ◽  
Real Data ◽  
Heavy Tail ◽  
Statistical Properties ◽  
Likelihood Method ◽  
Model Parameters ◽  
Data Sets ◽  
New Family

This work introduces a new one-parameter compound G family. Relevant statistical properties are derived. The new density can be “asymmetric right skewed with one peak and a heavy tail”, “symmetric” and “left skewedwith one peak”. The new hazard function can be “upside-down”, “upside-down-constant”, “increasing”, “decreasing” and “decreasing-constant”. Many bivariate types have been also derived via different common copulas. The estimation of the model parameters is performed by maximum likelihood method. The usefulness and flexibility of the new family is illustrated by means of two real data sets.

scholarly journals Some Properties and Estimation of Parameters for the Five Parameter Type I Generalized Half Logistic Distribution under Complete Observation

2020 ◽  
pp. 39-46
Author(s):  
O. A. Bello ◽  
P. O. Awodutire ◽  
I. Sule ◽  
H. O. Lawal
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Method ◽  
Likelihood Method ◽  
Logistic Distribution ◽  
Type I ◽  
Lifetime Data ◽  
Estimation Of Parameters ◽  
Distribution Estimation ◽  
Complete Observation

This paper is a further study of the five parameter type I generalized half logistic distribution. We derived some properties of the distribution. Estimation of the parameters of the distribution under complete observation was studied using the maximum likelihood method. To assess the flexibility of the distribution, it was applied to a real lifetime data and the results when compared to the sub-models showed that the five parameter type I generalized half logistic distribution performed best.

scholarly journals Estimation of parameters of Nadarajah-Haghighi extension of the exponential distribution using perfect and imperfect ranked set sample

2020 ◽  
Vol 30 (2) ◽  
pp. 177-198
Author(s):  
Marija Minic
Keyword(s):  
Maximum Likelihood ◽  
Exponential Distribution ◽  
Maximum Likelihood Method ◽  
Likelihood Method ◽  
Simple Random Sample ◽  
Estimation Of Parameters ◽  
Ranked Set Sample ◽  
Scale Parameters ◽  
Wide Range ◽  
Mean Square Errors

The ranked set sampling (RSS) is a cost-effective method of sampling that can be used in a wide range of statistical problems. In this paper, the shape and the scale parameters of Nadarajah-Haghighi extension of the exponential distribution are estimated based on a simple random sample (SRS) and RSS. Three cases are considered: 1) the scale parameter is known; 2) the shape parameter is known; 3) both shape and scale parameters are unknown. Observations are done when the ranking mechanism in the ranked set sample is perfect and when it is not. Method of moments, the maximum likelihood method, and a modification of the maximum likelihood method are used. The obtained estimators are compared in terms of their biases and mean square errors (MSE). The results revealed that estimators based on RSS tend to show better properties (smaller bias and MSE) relative to their SRS counterparts, regardless of the quality of the ranking.

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