Statistical Inference on a Finite Mixture of Exponentiated Kumaraswamy-G Distributions with Progressive Type II Censoring Using Bladder Cancer Data

A new family of distributions called the mixture of the exponentiated Kumaraswamy-G (henceforth, in short, ExpKum-G) class is developed. We consider Weibull distribution as the baseline (G) distribution to propose and study this special sub-model, which we call the exponentiated Kumaraswamy Weibull distribution. Several useful statistical properties of the proposed ExpKum-G distribution are derived. Under the classical paradigm, we consider the maximum likelihood estimation under progressive type II censoring to estimate the model parameters. Under the Bayesian paradigm, independent gamma priors are proposed to estimate the model parameters under progressive type II censored samples, assuming several loss functions. A simulation study is carried out to illustrate the efficiency of the proposed estimation strategies under both classical and Bayesian paradigms, based on progressively type II censoring models. For illustrative purposes, a real data set is considered that exhibits that the proposed model in the new class provides a better fit than other types of finite mixtures of exponentiated Kumaraswamy-type models

Statistical Inference on a Finite Mixture of Exponentiated Kumaraswamy-G Distributions with Progressive Type II Censoring Using Bladder Cancer Data

A new family of distributions called the mixture of the exponentiated Kumaraswamy-G (henceforth, in short, ExpKum-G) class is developed. We consider Weibull distribution as the baseline (G) distribution to propose and study this special sub-model, which we call the exponentiated Kumaraswamy Weibull distribution. Several useful statistical properties of the proposed ExpKum-G distribution are derived. Under the classical paradigm, we consider the maximum likelihood estimation under progressive type II censoring to estimate the model parameters. Under the Bayesian paradigm, independent gamma priors are proposed to estimate the model parameters under progressive type II censored samples, assuming several loss functions. A simulation study is carried out to illustrate the efficiency of the proposed estimation strategies under both classical and Bayesian paradigms, based on progressively type II censoring models. For illustrative purposes, a real data set is considered that exhibits that the proposed model in the new class provides a better fit than other types of finite mixtures of exponentiated Kumaraswamy-type models

Comparison of the diagnostic performance of microscopic examination, Copro-ELISA, and Copro-PCR in the diagnosis of Capillaria philippinensis infections.

Intestinal capillariasis is a parasitic zoonosis caused by the tiny nematode parasite Capillaria philippinensis. It is a major health problem that may lead to death if not diagnosed and treated appropriately. The difficulties in the diagnosis of C. philippinensis highlight the importance of developing accurate, sensitive, and specific methods for early diagnosis. This study aimed to detect the presence of C. philippinensis infection among 42 clinically suspected patients with certain criteria that are highly suggestive of capillariasis and to compare the diagnostic yield of microscopy, copro-ELISA, and PCR for the detection of copro-DNA. Sociodemographic characteristics and clinical data were also described for the infected group. Out of 42 patients, 10 were microscopically positive, 40 samples were positive by copro-ELISA, nested PCR detected 35 positive cases, with total detection rates of 23.8%, 95.2%, and 83.3% using direct microscopic examination, copro-ELISA, and PCR, respectively. The majority of positive cases were females, middle-aged people, and people from rural areas. The real number of cases infected with C. philippinensis may far exceed those estimated using microscopy. The diagnosis by copro-ELISA for the detection of C. philippinensis coproantigen and by nested PCR to identify parasite DNA revealed a higher number of positive cases. Using ELISA for the detection of coproantigen is a sensitive test that identifies the infection, yet it is not specific. Copro-DNA offers a satisfactory sensitive and specific method for the detection of infection in clinically suspected patients. The most susceptible individuals to C. philippinensis infection are females, middle-aged people, and people of low social standards. Intestinal capillariasis needs to be considered in patients who present with symptoms of chronic diarrhea and hypoalbuminemia because if these cases are left undiagnosed and untreated, they may suffer from lethal complications