Statistical Inference of Kumaraswamy Distribution under Imprecise Information
نویسندگان
چکیده
منابع مشابه
Inference on the Kumaraswamy distribution
Many lifetime distribution models have successfully served as population models for risk analysis and reliability mechanisms. The Kumaraswamy distribution is one of these distributions which is particularly useful to many natural phenomena whose outcomes have lower and upper bounds or bounded outcomes in the biomedical and epidemiological research. This paper studies point estimation and interv...
متن کاملInference on the Log-Exponentiated Kumaraswamy Distribution
In this paper, the log-exponentiated Kumaraswamy (LEK) distribution is introduced and studied as a survival model of unemployment, its survived function has the interesting property that it can be decreasing depending on the shape parameters. The method of maximum likelihood is applied for estimating the model parameters, survival and hazard rate functions. Stratification is used to reduce hete...
متن کاملStatistical Estimation Based on Generalized Order Statistics from Kumaraswamy Distribution
The Kumaraswamy distribution is similar to the Beta distribution but has the key advantage of a closed-form cumulative distribution function. In this paper we present the estimation of Kumaraswamy distribution parameters based on Generalized Order Statistics (GOS) using Maximum Likelihood Estimators (MLE). We proved that the parameters estimation for Kumaraswamy distribution can not be obtained...
متن کاملThe Kumaraswamy-geometric distribution
In this paper, the Kumaraswamy-geometric distribution, which is a member of the T -geometric family of discrete distributions is defined and studied. Some properties of the distribution such as moments, probability generating function, hazard and quantile functions are studied. The method of maximum likelihood estimation is proposed for estimating the model parameters. Two real data sets are us...
متن کاملStatistical Inference for the Lomax Distribution under Progressively Type-II Censoring with Binomial Removal
This paper considers parameter estimations in Lomax distribution under progressive type-II censoring with random removals, assuming that the number of units removed at each failure time has a binomial distribution. The maximum likelihood estimators (MLEs) are derived using the expectation-maximization (EM) algorithm. The Bayes estimates of the parameters are obtained using both the squared erro...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Biometrics & Biostatistics
سال: 2017
ISSN: 2155-6180
DOI: 10.4172/2155-6180.1000378