On a Multivariate Pareto Distribution: Estimation Methods

2012 ◽  
Author(s):  
Vali Alexandru Asimit ◽  
Edward Furman ◽  
Raluca Vernic
Keyword(s):  
Pareto Distribution ◽  
Estimation Methods ◽  
Distribution Estimation

scholarly journals Marshall-Olkin Generalized Pareto Distribution: Bayesian and Non Bayesian Estimation

2020 ◽  
pp. 21-33 ◽  
Author(s):  
Hanan Haj AHmad ◽  
Ehab Almetwally
Keyword(s):  
Loss Function ◽  
Bayesian Method ◽  
Pareto Distribution ◽  
Generalized Pareto Distribution ◽  
Least Square Method ◽  
Least Square ◽  
Estimation Methods ◽  
Model Parameters ◽  
Type I ◽  
Generalized Pareto

A new generalization of generalized Pareto Distribution is obtained using the generator Marshall-Olkin distribution (1997). The new distribution MOGP is more flexible and can be used to model non-monotonic failure rate functions. MOGP includes six different sub models: Generalized Pareto, Exponential, Uniform, Pareto type I, Marshall-Olkin Pareto and Marshall-Olkin exponential distribution. We consider different estimation procedures for estimating the model parameters, namely: Maximum likelihood estimator, Maximum product spacing, Least square method, weighted least square method and Bayesian Method. The Bayesian Method is considered under quadratic loss function and Linex loss function. Simulation analysis using MCMC technique is performed to compare between the proposed point estimation methods. The usefulness of MOGP is illustrated by means of real data set, which shows that this generalization is better fit than Pareto, GP and MOP distributions.

On Some Estimation Methods for the Inverse Pareto Distribution

2021 ◽  
Author(s):  
Indrajeet Kumar ◽  
Shishir Kumar Jha ◽  
Kapil Kumar
Keyword(s):  
Pareto Distribution ◽  
Estimation Methods

The inverted Nadarajah–Haghighi distribution: estimation methods and applications

2018 ◽  
Vol 88 (14) ◽  
pp. 2775-2798 ◽  
Author(s):  
M. H. Tahir ◽  
Gauss M. Cordeiro ◽  
Sajid Ali ◽  
Sanku Dey ◽  
Aroosa Manzoor
Keyword(s):  
Estimation Methods ◽  
Distribution Estimation

scholarly journals The Combined-Unified Hybrid Censored Samples from Pareto Distribution: Estimation and Properties

2021 ◽  
Vol 11 (13) ◽  
pp. 6000
Author(s):  
Khalaf S. Sultan ◽  
Walid Emam
Keyword(s):  
Maximum Likelihood ◽  
Pareto Distribution ◽  
Maximum Likelihood Estimators ◽  
Real Data ◽  
Maximum Likelihood Estimates ◽  
Unknown Parameters ◽  
Hazard Functions ◽  
Hybrid Censoring ◽  
Censored Samples ◽  
Distribution Estimation

In this paper, we use the combined-unified hybrid censoring samples to obtain the maximum likelihood estimates of the unknown parameters, survival, and hazard functions of Pareto distribution. Next, we discuss some efficiency criteria of the maximum likelihood estimators, including; the unbiasedness, consistency, and sufficiency. Additionally, we use MCMC to obtain the Bayesian estimates of the unknown parameters. In addition, we calculate the intervals estimation of the unknown parameters. Finally, we analyze a set of real data in view of the theoretical findings of the paper.

scholarly journals Inference Based on Type-II Hybrid Censored Data from a Pareto Distribution

2020 ◽  
Author(s):  
Çağatay Çetinkaya
Keyword(s):  
Censored Data ◽  
Pareto Distribution ◽  
Bayes Estimation ◽  
Estimation Methods ◽  
Type Ii ◽  
Simulation Studies ◽  
Shape Parameters ◽  
Hybrid Censoring ◽  
Approximate Confidence Intervals ◽  
Censoring Scheme

The Pareto distribution takes part in life-testing experiments as a finite range distribution. In this study, inference studies for the scale and shape parameters of the Pareto distribution under type-II hybrid censoring scheme are considered. The main reason for choosing this censoring scheme is its advantage of guaranteeing at least particular failures to be observed by the end of the experiment. Maximum likelihood and Bayes estimation methods are used with their approximate confidence intervals. Proposed estimation methods are compared numerically based on simulation studies. A numerical example is also used to illustrate the theoretical outcomes.

scholarly journals A Cluster Truncated Pareto Distribution and Its Applications

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Mei Ling Huang ◽  
Vincenzo Coia ◽  
Percy Brill
Keyword(s):  
Real World ◽  
Goodness Of Fit ◽  
Pareto Distribution ◽  
Estimation Method ◽  
Estimation Methods ◽  
Real World Data ◽  
Goodness Of Fit Tests ◽  
Heavy Tailed Distribution ◽  
Heavy Tailed ◽  
Truncated Pareto

The Pareto distribution is a heavy-tailed distribution with many applications in the real world. The tail of the distribution is important, but the threshold of the distribution is difficult to determine in some situations. In this paper we consider two real-world examples with heavy-tailed observations, which leads us to propose a mixture truncated Pareto distribution (MTPD) and study its properties. We construct a cluster truncated Pareto distribution (CTPD) by using a two-point slope technique to estimate the MTPD from a random sample. We apply the MTPD and CTPD to the two examples and compare the proposed method with existing estimation methods. The results of log-log plots and goodness-of-fit tests show that the MTPD and the cluster estimation method produce very good fitting distributions with real-world data.

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