(2018). Parameter Estimation for the Kumaraswamy Distribution Based on Hybrid Censoring. American Journal of Mathematical and Management Sciences: Vol. 37, No. 3, pp. 243-261. Parameter estimation, using different methods, namely methods of moments, maximum likelihood and proportion, is discussed. In this paper, a discrete inverted Kumaraswamy distribution; This paper addresses different methods of estimation of the unknown parameters of a two-parameter Kumaraswamy distribution from a frequentist point of view. We briefly describe ten different frequentist approaches, namely, maximum likelihood estimators, moments estimators, L-moments estimators In this paper, we introduce and study a new three-parameter lifetime distribution constructed from the so-called type I half-logistic-G family and the inverted Kumaraswamy distribution, naturally called the type I half-logistic inverted Kumaraswamy distribution. The main feature of this new distribution is to add a new tuning parameter to the inverted Kumaraswamy (according to the type I half (2018). Parameter Estimation for the Kumaraswamy Distribution Based on Hybrid Censoring. American Journal of Mathematical and Management Sciences: Vol. 37, No. 3, pp. 243-261. DOI: 10.4314/IJEST.V3I9.4 Corpus ID: 67779827. Bayesian estimations in the Kumaraswamy distribution under progressively type II censoring data @article{Gholizadeh2012BayesianEI, title={Bayesian estimations in the Kumaraswamy distribution under progressively type II censoring data}, author={R. Gholizadeh and M. Khalilpor and M. Hadian}, journal={International journal of engineering science and Search text. Search type Research Explorer Website Staff directory. Alternatively, use our A–Z index : log-Kumaraswamy distribution, maximum likelihood estimation, Cramer-von-Mises estimation method, least-squares estimation, percentile estimation, Monte-Carlo simulation. Introduction. Log-Kumaraswamy (LKw) distribution is a special case of log-exponentiated Ku-maraswamy distribution proposed by Lemonte . et al. [1]. They have generated LKw distribution Firstly, it is described six different estimation methods such as maximum likelihood, approximate bayesian, least-squares, weighted least-squares, percentile, and Cramer-von-Mises. We have considered estimation of the parameters of the Kumaraswamy distribution using ten methods, namely, maximum likelihood estimation, moments estimation, L-moments estimation, percentile estimation, least squares estimation, weighted least squares estimation, maximum product of spacings estimation, Cramér–von Mises estimation, Anderson–Darling estimation and right-tailed Anderson–Darling estimation. It is not feasible to compare these methods theoretically.
[index] [5642] [7415] [1713] [4664] [6069] [4065] [8224] [5401] [3595] [2001]
Copyright © 2024 top100.onlinetoprealmoneygame.xyz