Estimation for Akshaya Failure Model with Competing Risks under Progressive Censoring Scheme with Analyzing of Thymic Lymphoma of Mice Application

Table 1

Chronological review on competing risk models under progressive censoring scheme and their baseline distributions.

S. no.	Developers (year)	Competing risk model based on progressive censoring scheme
1	Debasis et al. (2003)	Discussed the analysis of progressively censored competing risks data [36].
2	Pareek et al. (2009)	Explored the application of Weibull distribution to compting risk model under progressive censoring scheme [37].
3	Debasis and Biswabrata (2011)	Discussed the Bayesian analysis of progressive censored competing risks data [38].
4	Bundel et al. (2016)	Applied the inverse Lindley distribution for modeling competing risks for progressive censored data [39].
5	Kumar et al. (2016)	Studied the Bayesian analysis of modified Weibull distribution under progressive censored competing risk model [40].
6	Liang (2018)	Used the kumaraswamy distribution to model competing risk data under progressive censored data [41].
7	Hongyi and Wenhao (2019)	Used the Rayleigh distribution to model competing risk data under progressive type-II censored data [42].
8	Manoj and Rakhi (2019)	Presented the Bayesian analysis of Weibull distribution based on progressive type-II censored competing risks data with binomial removals [43].
9	Ahmed et al. (2020)	Introduced the inference of progressive type-II censored competing risks data from chen distribution [44].
10	Fariba et al. (2020)	Presented the inference for competing risks model under progressive interval censored using Weibull data [45].
11	Shuhan and Wenhao (2020)	Discussed the estimation of the parameters of the two-parameter Rayleigh distribution based on adaptive type-II progressive hybrid censored data with competing risks [46].
12	Chandrakant et al. (2021)	Presented the analysis of a progressively censored competing risks data using gompertz distribution [47].
13	El-Rahem et al. (2021)	Used the extension of the exponential distribution to model competing risk under progressive censoring scheme [48].
14	Almarashi et al. (2021)	Used exponential lifetimes for modeling competing risk model with the presence of joint hybrid censoring scheme [10].
15	Elshahhat (2021)	Introduced using Xgamma under type-II adaptive progressive hybrid censoring
16	Kumar et al. (2021)	Presented the inference for partially observed competing risks model for kumaraswamy distribution under generalized progressive hybrid censoring [49].
17	Yuge and Wenhao. (2022)	Presented Burr-XII distribution under adaptive type-II progressive censored schemes with the presence of competing risks data [50].
18	Qi et al. (2022)	Presented the statistical inference for the gompertz distribution under general progressive type-II censored competing risks sample [51].