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Journal articles on the topic 'Exponentiated exponential distribution'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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1

Pogány, Tibor, and Abdus Saboor. "The gamma exponentiated exponential-Weibull distribution." Filomat 30, no. 12 (2016): 3159–70. http://dx.doi.org/10.2298/fil1612159p.

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Anewfour-parameter model called the gamma-exponentiated exponential-Weibull distribution is being introduced in this paper. The new model turns out to be quite flexible for analyzing positive data. Representations of certain statistical functions associated with this distribution are obtained. Some special cases are pointed out as well. The parameters of the proposed distribution are estimated by making use of the maximum likelihood approach. This density function is utilized to model two actual data sets. The new distribution is shown to provide a better fit than related distributions as meas

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2

Rodrigues, Jailson, and Ana Silva. "The Exponentiated Kumaraswamy-Exponential Distribution." British Journal of Applied Science & Technology 10, no. 5 (2015): 1–12. http://dx.doi.org/10.9734/bjast/2015/16935.

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3

Ristić, Miroslav M., and Narayanaswamy Balakrishnan. "The gamma-exponentiated exponential distribution." Journal of Statistical Computation and Simulation 82, no. 8 (2012): 1191–206. http://dx.doi.org/10.1080/00949655.2011.574633.

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4

Nasiru, Suleman, Peter N. Mwita, and Oscar Ngesa. "Exponentiated generalized exponential Dagum distribution." Journal of King Saud University - Science 31, no. 3 (2019): 362–71. http://dx.doi.org/10.1016/j.jksus.2017.09.009.

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5

Sarhan, Ammar M., Abd EL-Baset A. Ahmad, and Ibtesam A. Alasbahi. "Exponentiated generalized linear exponential distribution." Applied Mathematical Modelling 37, no. 5 (2013): 2838–49. http://dx.doi.org/10.1016/j.apm.2012.06.019.

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6

Louzada, Francisco, Vitor Marchi, and James Carpenter. "The Complementary Exponentiated Exponential Geometric Lifetime Distribution." Journal of Probability and Statistics 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/502159.

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We proposed a new family of lifetime distributions, namely, complementary exponentiated exponential geometric distribution. This new family arises on a latent competing risk scenario, where the lifetime associated with a particular risk is not observable but only the maximum lifetime value among all risks. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulas for its survival and hazard functions, moments,rth moment of theith order statistic, mean residual lifetime, and modal value. Inference is i

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7

Nasiru, Suleman, Bol A. M. Atem, and Kwara Nantomah. "Poisson Exponentiated Erlang-Truncated Exponential Distribution." Journal of Statistics Applications & Probability 7, no. 2 (2018): 245–61. http://dx.doi.org/10.18576/jsap/070203.

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8

Pogány, Tibor K. "The exponentiated exponential Poisson distribution revisited." Statistics 49, no. 4 (2014): 918–29. http://dx.doi.org/10.1080/02331888.2014.932794.

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9

Nadarajah, Saralees. "The exponentiated exponential distribution: a survey." AStA Advances in Statistical Analysis 95, no. 3 (2011): 219–51. http://dx.doi.org/10.1007/s10182-011-0154-5.

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10

Andrade, Thiago A. N. de, Marcelo Bourguignon, and Gauss M. Cordeiro. "The exponentiated generalized extended exponential distribution." Journal of Data Science 14, no. 3 (2021): 393–414. http://dx.doi.org/10.6339/jds.201607_14(3).0001.

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11

Makubate, Boikanyo, Broderick O. Oluyede, Neo Dingalo, and Adeniyi Francis Fagbamigbe. "The Beta Log-Logistic Weibull Distribution: Model, Properties and Application." International Journal of Statistics and Probability 7, no. 6 (2018): 49. http://dx.doi.org/10.5539/ijsp.v7n6p49.

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We propose and develop the properties of a new generalized distribution called the beta log-logistic Weibull (BLLoGW) distribution. This model contain several new distributions such as beta log-logistic Rayleigh, beta log-logistic exponential, exponentiated log-logistic Weibull, exponentiated log-logistic Rayleigh, exponentiated log-logistic exponential,&nbsp; log-logistic Weibull, log-logistic Rayleigh and log-logistic distributions as special cases. Structural properties of this generalized distribution including series expansion of the probability density function and cumulative distrib

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12

Fatima, Kawsar, and S. P. Ahmad. "Bayesian Analysis of Exponentiated Inverted Exponential Distribution." Sohag Journal of Mathematics 5, no. 1 (2018): 35–42. http://dx.doi.org/10.18576/sjm/050106.

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13

Bakouch, Hassan S., Miroslav M. Ristić, A. Asgharzadeh, L. Esmaily, and Bander M. Al-Zahrani. "An exponentiated exponential binomial distribution with application." Statistics & Probability Letters 82, no. 6 (2012): 1067–81. http://dx.doi.org/10.1016/j.spl.2012.03.004.

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14

Salem, Hanaa Abd El-Reheem. "EXPONENTIATED EXPONENTIAL PARETO DISTRIBUTION: PROPERTIES AND ESTIMATION." Advances and Applications in Statistics 57, no. 1 (2019): 89–104. http://dx.doi.org/10.17654/as057010089.

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15

Kwong, Hok Shing, and Saralees Nadarajah. "On the Generalized Exponentiated Exponential Lindley Distribution." Journal of Data Science 17, no. 2 (2021): 363–82. http://dx.doi.org/10.6339/jds.201904_17(2).0007.

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16

Eissa, Fathy Helmy. "The Exponentiated Kumaraswamy-Weibull Distribution with Application to Real Data." International Journal of Statistics and Probability 6, no. 6 (2017): 167. http://dx.doi.org/10.5539/ijsp.v6n6p167.

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A new five-parameter lifetime distribution called the exponentiated Kumaraswamy-Weibull distribution is introduced. It includes several important sub-models as special cases such as exponentiated Weibull, Kumaraswamy-Weibull, exponentiated exponential, exponentiated Rayleigh and Weibull. Essential mathematical and statistical properties for the distribution are presented. A proximate form of the mode is derived and it can be used to derive mode forms of other well-known distributions. Important parametric characterizations for probability density and hazard functions are discussed. The estimat

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17

Dessoky, Shimaa A., and Ahmed M. T. Abd El-Bar. "A New Five Parameter Lifetime Distribution: Properties and Application." JOURNAL OF ADVANCES IN MATHEMATICS 13, no. 3 (2017): 7205–18. http://dx.doi.org/10.24297/jam.v13i3.6045.

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This paper deals with a new generalization of the Weibull distribution. This distribution is called exponentiated exponentiated exponential-Weibull (EEE-W) distribution. Various structural properties of the new probabilistic model are considered, such as hazard rate function, moments, moment generating function, quantile function, skewness, kurtosis, Shannon entropy and RÃ©nyi entropy. The maximum likelihood estimates of its unknown parameters are obtained. Finally, areal data set is analyzed and it observed that the present distribution can provide a better fit than some other known distribut

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18

EAbu-Youssef, S., B. I Mohammed, and M. G Sief. "An Extended Exponentiated Exponential Distribution and its Properties." International Journal of Computer Applications 121, no. 5 (2015): 1–6. http://dx.doi.org/10.5120/21533-4518.

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19

E.Mohammed, B. "Statistical Properties of Kumaraswamy-Generalized Exponentiated Exponential Distribution." International Journal of Computer Applications 94, no. 4 (2014): 1–8. http://dx.doi.org/10.5120/16328-5602.

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20

Al-Sulami, Dawlah. "Exponentiated Exponential Weibull Distribution: Mathematical Properties and Application." American Journal of Applied Sciences 17, no. 1 (2020): 188–95. http://dx.doi.org/10.3844/ajassp.2020.188.195.

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21

Sapkota, Laxmi Prasad. "Exponentiated–Exponential Logistic Distribution: Some Properties and Application." Janapriya Journal of Interdisciplinary Studies 9, no. 1 (2020): 100–108. http://dx.doi.org/10.3126/jjis.v9i1.35280.

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This study proposes new distribution which is generated from exponentiated-exponential-X family of distribution. It is explored various shape and behavior of the observed distribution through probability density plot, hazard rate function and quantile function. Further we have investigated some mathematical properties, estimation of the parameters and associated confidence interval using maximum likelihood estimation (MLE) method of the exponentiatedexponential-logistic distribution (EELD).

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22

Abouelmagd, T. H. M. "The Logarithmic Burr-Hatke Exponential Distribution for Modeling Reliability and Medical Data." International Journal of Statistics and Probability 7, no. 5 (2018): 73. http://dx.doi.org/10.5539/ijsp.v7n5p73.

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In this work, we introduced a new one-parameter exponential distribution. Some of its structural properties are derived% \textbf{.} The maximum likelihood method is used to estimate the model parameters by means of numerical Monte Carlo simulation study. The justification for the practicality of the new lifetime model is based on the wider use of the exponential model. The new model can be viewed as a mixtureof the exponentiated exponential distribution. It can also be considered as a suitable model for fitting right skewed data.\textbf{\ }We prove empirically the importance and flexibility of

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23

Roozegar, Rasool, and Ali Akbar Jafari. "ON BIVARIATE EXPONENTIATED EXTENDED WEIBULL FAMILY OF DISTRIBUTIONS." Ciência e Natura 38, no. 2 (2016): 564. http://dx.doi.org/10.5902/2179460x19496.

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In this paper, we introduce a new class of distributions by compounding the exponentiated extended Weibull family and power series family. This distribution contains several lifetime models such as the complementary extended Weibull-power series, generalized exponential-power series, generalized linear failure rate-power series, exponentiated Weibull-power series, generalized modifiedWeibull-power series, generalized Gompertz-power series and exponentiated extendedWeibull distributions as special cases. We obtain several properties of this new class of distributions such as Shannon entropy, me

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24

Makubate, Boikanyo, Broderick O. Oluyede, Gofaone Motobetso, Shujiao Huang, and Adeniyi F. Fagbamigbe. "The Beta Weibull-G Family of Distributions: Model, Properties and Application." International Journal of Statistics and Probability 7, no. 2 (2018): 12. http://dx.doi.org/10.5539/ijsp.v7n2p12.

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A new family of generalized distributions called the beta Weibull-G (BWG) distribution is proposed and developed. This new class of distributions has several new and well known distributions including exponentiated-G, Weibull-G, Rayleigh-G, exponential-G, beta exponential-G, beta Rayleigh-G, beta Rayleigh exponential, beta-exponential-exponential, Weibull-log-logistic distributions, as well as several other distributions such as beta Weibull-Uniform, beta Rayleigh-Uniform, beta exponential-Uniform, beta Weibull-log logistic and beta Weibull-exponential distributions as special cases. Series ex

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25

El Haroun, Neema Mohamed. "Partial Generalized Probability Weighted Moments for Exponentiated Exponential Distribution." Pakistan Journal of Statistics and Operation Research 11, no. 3 (2015): 299. http://dx.doi.org/10.18187/pjsor.v11i3.729.

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26

Nasiru, Suleman, Albert Luguterah, and Kwara Nantomah. "The Exponentiated Kumaraswamy Linear Exponential Distribution: Theory and Application." Sohag Journal of Mathematics 5, no. 1 (2018): 1–8. http://dx.doi.org/10.18576/sjm/050101.

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27

KUMAR, Devendra. "Moments and Estimation of the Exponentiated Moment Exponential Distribution." Mathematical Sciences and Applications E-Notes 4, no. 1 (2016): 94–112. http://dx.doi.org/10.36753/mathenot.421415.

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28

Usman, Umar, Suleiman Shamsuddeen, Bello Magaji Arkilla, and Yakubu Aliyu. "Inferences on the Weibull Exponentiated Exponential Distribution and Applications." International Journal of Statistical Distributions and Applications 6, no. 1 (2020): 10. http://dx.doi.org/10.11648/j.ijsd.20200601.12.

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29

MIHOC, ION, and CRISTINA-IOANA FATU. "On the comparison of fisher information of some probability distributions." Carpathian Journal of Mathematics 30, no. 3 (2014): 345–53. http://dx.doi.org/10.37193/cjm.2014.03.09.

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In 1998 Gupta, R. C., Gupta, P. L. and Gupta, R. D. have introduced the exponentiated exponential distribution (or the generalized exponential distribution) as a generalization of the standard exponential distribution. The mathematical properties of this distribution have been studied in detail by Gupta and Kundu (2001). The aim of this paper is to establish some relations concerning the Fisher’s information of the generalized exponential distribution and the similar information corresponding in the case of the weighted version.

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30

Shahzad, Mirza Naveed, Ehsan Ullah, and Abid Hussanan. "Beta Exponentiated Modified Weibull Distribution: Properties and Application." Symmetry 11, no. 6 (2019): 781. http://dx.doi.org/10.3390/sym11060781.

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One of the most prominent statistical distributions is the Weibull distribution. The recent modifications in this distribution have enhanced its application but only in specific fields. To introduce a more generalized Weibull distribution, in this work beta exponentiated modified Weibull distribution is established. This distribution consolidate the exponential, skewed and symmetric shapes into one density. The proposed distribution also contains nineteen lifetime distributions as a special case, which shows the flexibility of the distribution. The statistical properties of the proposed model

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31

Badr, Majdah M. "The exponentiated exponential burr XII distribution: Theory and application to lifetime data." Journal of Intelligent & Fuzzy Systems 40, no. 3 (2021): 4207–21. http://dx.doi.org/10.3233/jifs-200819.

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Lifetime data collected from reliability tests are among data that often exhibit significant heterogeneity caused by variations in manufacturing which make standard lifetime models inadequate. In this paper we introduce a new lifetime distribution derived from T-X family technique called exponentiated exponential Burr XII (EE-BXII) distribution. We establish various mathematical properties. The maximum likelihood estimates (MLE) for the EE-BXII parameters are derived. We estimate the precision of the maximum likelihood estimators via simulation study. Some numerical illustrations are performed

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32

Ibrahim, Sule, Sani Ibrahim Doguwa, Audu Isah, and Haruna Muhammad Jibril. "On the Flexibility of Topp Leone Exponentiated Inverse Exponential Distribution." International Journal of Data Science and Analysis 6, no. 3 (2020): 83. http://dx.doi.org/10.11648/j.ijdsa.20200603.12.

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33

Almarashi, Abdullah M., Mohamed G. Khalil, M. Elgarhy, and Mamhoud M. ElSehetry. "EXPONENTIATED HALF LOGISTIC EXPONENTIAL DISTRIBUTION WITH STATISTICAL PROPERTIES AND APPLICATIONS." Advances and Applications in Statistics 53, no. 4 (2018): 423–40. http://dx.doi.org/10.17654/as053040423.

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34

Poonia, Neeraj, and Sarita Azad. "A New Exponentiated Generalized Linear Exponential Distribution: Properties and Application." RMS: Research in Mathematics & Statistics 8, no. 1 (2021): 1953233. http://dx.doi.org/10.1080/27658449.2021.1953233.

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35

Braimah, J. O., J. A. Adjekukor, N. Edike, and S. O. Elakhe. "A new Weibull Exponentiated Inverted Weibull Distribution for modelling positively-skewed data." Global Journal of Pure and Applied Sciences 27, no. 1 (2021): 43–53. http://dx.doi.org/10.4314/gjpas.v27i1.6.

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An Exponentiated Inverted Weibull Distribution (EIWD) has a hazard rate (failure rate) function that is unimodal, thus making it less efficient for modeling data with an increasing failure rate (IFR). Hence, the need to generalize the EIWD in order to obtain a distribution that will be proficient in modeling these types of dataset (data with an increasing failure rate). This paper therefore, extends the EIWD in order to obtain Weibull Exponentiated Inverted Weibull (WEIW) distribution using the Weibull-Generator technique. Some of the properties investigated include the mean, variance, median,

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36

Badr, Majdah, and Muhammad Ijaz. "The Exponentiated Exponential Burr XII distribution: Theory and application to lifetime and simulated data." PLOS ONE 16, no. 3 (2021): e0248873. http://dx.doi.org/10.1371/journal.pone.0248873.

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The paper addresses a new four-parameter probability distribution called the Exponentiated Exponential Burr XII or abbreviated as EE-BXII. We derive various statistical properties in addition to the parameter estimation, moments, and asymptotic confidence bounds. We estimate the precision of the maximum likelihood estimators via a simulation study. Furthermore, the utility of the proposed distribution is evaluated by using two lifetime data sets and the results are compared with other existing probability distributions. The results clarify that the proposed distribution provides a better fit t

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37

Al-Marzouki, Sanaa, and Sharifah Alrajhi. "A New-Flexible Generated Family of Distributions Based on Half-Logistic Distribution." Journal of Computational and Theoretical Nanoscience 17, no. 11 (2020): 4813–18. http://dx.doi.org/10.1166/jctn.2020.9332.

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We proposed a new family of distributions from a half logistic model called the generalized odd half logistic family. We expressed its density function as a linear combination of exponentiated densities. We calculate some statistical properties as the moments, probability weighted moment, quantile and order statistics. Two new special models are mentioned. We study the estimation of the parameters for the odd generalized half logistic exponential and the odd generalized half logistic Rayleigh models by using maximum likelihood method. One real data set is assesed to illustrate the usefulness o

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38

Loganathan, A., and M. Gunasekaran. "Construction of Reliability Single Sampling Plans Based on Exponentiated Exponential Distribution." Journal of Testing and Evaluation 47, no. 2 (2018): 20160594. http://dx.doi.org/10.1520/jte20160594.

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39

Mohammed, Heba S., Saieed F. Ateya, and Essam K. AL-Hussaini. "Estimation based on progressive first-failure censoring from exponentiated exponential distribution." Journal of Applied Statistics 44, no. 8 (2016): 1479–94. http://dx.doi.org/10.1080/02664763.2016.1214245.

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40

صالح, سیده. "sample size determination for follow up studies of exponentiated exponential distribution." المجلة العملیة التجارة والتمویل 29, no. 1 (2009): 11–25. http://dx.doi.org/10.21608/caf.2009.138836.

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41

Cordeiro, Gauss, M. Zubair, and M. Mansoor. "A Study of the Logistic Exponentiated-Exponential Distribution and Its Applications." Journal of Advances in Applied & Computational Mathematics 7, no. 1 (2020): 38–48. http://dx.doi.org/10.15377/2409-5761.2020.07.6.

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42

Rao, G. Srinivasa, Sauda Mbwambo, and P. K. Josephat. "Estimation of Stress–Strength Reliability from Exponentiated Inverse Rayleigh Distribution." International Journal of Reliability, Quality and Safety Engineering 26, no. 01 (2019): 1950005. http://dx.doi.org/10.1142/s0218539319500050.

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This paper considers the estimation of stress–strength reliability when two independent exponential inverse Rayleigh distributions with different shape parameters and common scale parameter. The maximum likelihood estimator (MLE) of the reliability, its asymptotic distribution and asymptotic confidence intervals are constructed. Comparisons of the performance of the estimators are carried out using Monte Carlo simulations, the mean squared error (MSE), bias, average length and coverage probabilities. Finally, a demonstration is delivered on how the proposed reliability model may be applied in

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43

Kutal, Durga, and Lianfen Qian. "A Non-Mixture Cure Model for Right-Censored Data with Fréchet Distribution." Stats 1, no. 1 (2018): 176–88. http://dx.doi.org/10.3390/stats1010013.

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This paper considers a non-mixture cure model for right-censored data. It utilizes the maximum likelihood method to estimate model parameters in the non-mixture cure model. The simulation study is based on Fréchet susceptible distribution to evaluate the performance of the method. Compared with Weibull and exponentiated exponential distributions, the non-mixture Fréchet distribution is shown to be the best in modeling a real data on allogeneic marrow HLA-matched donors and ECOG phase III clinical trial e1684 data.

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44

Louzada, Francisco, Cintia Y. Yamachi, Vitor A. A. Marchi, and Maria A. P. Franco. "The long-term exponentiated complementary exponential geometric distribution under a latent complementary causes framework." TEMA (São Carlos) 15, no. 1 (2014): 019. http://dx.doi.org/10.5540/tema.2014.015.01.0019.

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<p><span>A new lifetime distribution which accommodates decreasing and unimodal hazard function is proposed in this paper. It is derived from the exponentiated complementary exponential geometric distribution and has it genesis on the compounding the exponential and geometric distributions. It can be used on a latent complementary causes scenario, where onle thethe minimum lifetime among all causes is observed. We derive the density, quantile, survival and failure rate functions for the proposed distribution, as well as some proprieties such as the characteristic function, mean, va

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45

Iqbal, Zafar, Muhammad Wasim, and Naureen Riaz. "EXPONENTIATED MOMENT EXPONENTIAL DISTRIBUTION AND POWER SERIES DISTRIBUTION WITH APPLICATIONS: A NEW COMPOUND FAMILY." International Journal of Advanced Research 5, no. 7 (2017): 1335–55. http://dx.doi.org/10.21474/ijar01/4844.

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46

Louzada, Francisco, Vitor Marchi, and Mari Roman. "The exponentiated exponential–geometric distribution: a distribution with decreasing, increasing and unimodal failure rate." Statistics 48, no. 1 (2012): 167–81. http://dx.doi.org/10.1080/02331888.2012.667103.

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47

Kumar, Devendra, Tanujit Dey, and Sanku Dey. "Statistical Inference of Exponentiated Moment Exponential Distribution Based on Lower Record Values." Communications in Mathematics and Statistics 5, no. 3 (2017): 231–60. http://dx.doi.org/10.1007/s40304-017-0110-0.

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48

Tripathi, Yogesh Mani, Tanmay Kayal, and Sanku Dey. "Estimation of the PDF and the CDF of exponentiated moment exponential distribution." International Journal of System Assurance Engineering and Management 8, S2 (2017): 1282–96. http://dx.doi.org/10.1007/s13198-017-0599-3.

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49

Afify, Ahmed Z., Ahmed M. Gemeay, and Noor Akma Ibrahim. "The Heavy-Tailed Exponential Distribution: Risk Measures, Estimation, and Application to Actuarial Data." Mathematics 8, no. 8 (2020): 1276. http://dx.doi.org/10.3390/math8081276.

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Modeling insurance data using heavy-tailed distributions is of great interest for actuaries. Probability distributions present a description of risk exposure, where the level of exposure to the risk can be determined by “key risk indicators” that usually are functions of the model. Actuaries and risk managers often use such key risk indicators to determine the degree to which their companies are subject to particular aspects of risk, which arise from changes in underlying variables such as prices of equity, interest rates, or exchange rates. The present study proposes a new heavy-tailed expone

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50

Al-Mofleh, Hazem, Ahmed Z. Afify, and Noor Akma Ibrahim. "A New Extended Two-Parameter Distribution: Properties, Estimation Methods, and Applications in Medicine and Geology." Mathematics 8, no. 9 (2020): 1578. http://dx.doi.org/10.3390/math8091578.

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In this paper, a new two-parameter generalized Ramos–Louzada distribution is proposed. The proposed model provides more flexibility in modeling data with increasing, decreasing, J-shaped, and reversed-J shaped hazard rate functions. Several statistical properties of the model were derived. The unknown parameters of the new distribution were explored using eight frequentist estimation approaches. These approaches are important for developing guidelines to choose the best method of estimation for the model parameters, which would be of great interest to practitioners and applied statisticians. D

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