Browsing by Author "Kirigiti, Peter Josephat"

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    Application of Odd Lomax log-logistic distribution to cancer data
    (Elsevier BV, 2024) Kailembo, Benson Benedicto; Gadde, Srinivasa Rao; Kirigiti, Peter Josephat
    The effectiveness of the parental distribution is modified in this article by adding flexibility, allowing it to capture all characteristics of the provided real-world data sets. This is accomplished by using the T-X class of distributions to generalize the parental distribution. Odd Lomax log-logistic distribution or OLLLD in short, is the name of the generalized parental distribution. The fundamental statistical properties of OLLLD are explicitly expressed. The maximum likelihood estimation approach is used to estimate the unidentified OLLLD parameters. In order to investigate the fit of the approach employed in estimating the parameters of OLLLD, the data are generated and an investigation done. Again, the ability of OLLLD is evaluated by fitting it to the real survival time data set of breast cancer.
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    Application of Odd Lomax log-logistic distribution to cancer data
    (Elsevier, 2024-03) Kailembo, Benson Benedicto; Gadde, Rao Srinivasa; Kirigiti, Peter Josephat
    The effectiveness of the parental distribution is modified in this article by adding flexibility, allowing it to capture all characteristics of the provided real-world data sets. This is accomplished by using the T-X class of distributions to generalize the parental distribution. Odd Lomax loglogistic distribution or OLLLD in short, is the name of the generalized parental distribution. The fundamental statistical properties of OLLLD are explicitly expressed. The maximum likelihood estimation approach is used to estimate the unidentified OLLLD parameters. In order to investigate the fit of the approach employed in estimating the parameters of OLLLD, the data are generated and an investigation done. Again, the ability of OLLLD is evaluated by fitting it to the real survival time data set of breast cancer.
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    Application of the multiple dependent state sampling strategy to late adolescent suicide rates
    (Springer Science and Business Media LLC, 2023) Kolli, Nagasaritha; Rosaiah, Kanaparthi; Rao, Gadde Srinivasa; Kirigiti, Peter Josephat
    A multiple dependent state sampling plan (MDSSP) is designed when the lifetimes of the variables follow New Lomax Rayleigh Distribution (NLRD). The decision to accept or reject a lot in the proposed methodology is based on the quality of the given present or previous lots. A binomial model-based operating characteristic curve (OC curve) for continuous lots of variables under similar settings in healthcare is used in finding the probability of acceptance, acceptance number, rejection number, and the number of preceding (succeeding) lots to consider. Time truncated life test based on the specified median of the NLRD is used in designing the current acceptance sampling plan. For specified values of the parameters of NLRD, quantile ratios, consumer’s risk and producer’s risk, average sampling number (ASN) and probability of acceptance of a lot are reported in tables. Real data on worldwide suicide rates of 15–19 years in the year 2019 from the World Health Organization (WHO) website is considered to illustrate this methodology. The minimum sample size required from the selected data to comment on worldwide suicide rates in late adolescents is explained with MDSSP. The results of the proposed acceptance sampling method are compared with the single-stage sampling plan.
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    Application of the multiple dependent state sampling strategy to late adolescent suicide rates
    (Springer Science and Business Media LLC, 2023-08-22) Kolli, Nagasaritha; Rosaiah, Kanaparthi; Rao, Gadde Srinivasa; Kirigiti, Peter Josephat
    A multiple dependent state sampling plan (MDSSP) is designed when the lifetimes of the variables follow New Lomax Rayleigh Distribution (NLRD). The decision to accept or reject a lot in the proposed methodology is based on the quality of the given present or previous lots. A binomial model-based operating characteristic curve (OC curve) for continuous lots of variables under similar settings in healthcare is used in finding the probability of acceptance, acceptance number, rejection number, and the number of preceding (succeeding) lots to consider. Time truncated life test based on the specified median of the NLRD is used in designing the current acceptance sampling plan. For specified values of the parameters of NLRD, quantile ratios, consumer’s risk and producer’s risk, average sampling number (ASN) and probability of acceptance of a lot are reported in tables. Real data on worldwide suicide rates of 15–19 years in the year 2019 from the World Health Organization (WHO) website is considered to illustrate this methodology. The minimum sample size required from the selected data to comment on worldwide suicide rates in late adolescents is explained with MDSSP. The results of the proposed acceptance sampling method are compared with the single-stage sampling plan.
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    Longitudinal Evaluation of the Influence of WORTH Yetu on Household Economic Status Based on the Count of Non-asset Resources for Orphaned and Vulnerable Children’s Well-being in Tanzania
    (Springer Science and Business Media LLC, 2024) Exavery, Amon; Kirigiti, Peter Josephat; Balan, Ramkumar T.; Charles, John
    This research uniquely focused on non-assets such as living conditions and children’s quality of life as important indicators of household socioeconomic status, especially in low-income settings where acquiring assets may be challenging. The study assessed the impact of an economic empowerment programme, WORTH Yetu, on economic well-being of households caring for orphaned and vulnerable children (OVC) in Tanzania. Based on longitudinal data from the USAID Kizazi Kipya project, we counted the available non-assets at the household level for OVC well-being, including shelter conditions, clothing quality, school and medical support, and savings within households. The study included 249,655 households (70% with female caregivers) at baseline, with 247,638 of them reached at the follow-up after an average of 1.6 years. Results showed that the mean number of non-assets increased from 0.86 at baseline to 1.04 at the follow-up. Notably, households that participated in the WORTH Yetu programme increased their mean count of non-assets to 1.37 while it was 1.00 among non-participants. In the multilevel mixed-effects Poisson regression model, WORTH Yetu participants were 48% more likely to experience an increase in non-assets at the follow-up compared to non-participants (adjusted incidence-rate ratio (aIRR) = 1.48 [1.46, 1.49]), with notable differences between households with female (aIRR = 1.45 [1.43, 1.47]) and male caregivers (aIRR = 1.53 [1.50, 1.57]). Overall, the WORTH Yetu programme significantly improved the count of non-assets for OVC well-being, but the observed differences in the non-assets based on the caregiver gender suggest varied outcomes for OVC, highlighting the necessity for further research.
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    Rating of cash crop insurance contracts in Tanzania using nonparametric methods
    (IGI Global, 2021) Massawe, Expery Mathias; Kirigiti, Peter Josephat; Mbwambo, Sauda Hatibu
    This chapter used nonparametric methods to establish the parameters of cash crop insurance contracts based on zone yields. The secondary historical yields data obtained from the Food and Agriculture Organization of the United Nations, for the period of 1961 through 2018, for cotton and cashew nuts, were used both in estimating the kernel density function and forecasting the mean yield. The estimated kernel density and mean forecasts were used to tabulate, at a different level of coverage, the probability of loss, the expected yield shortfall (kilogram per hectare, denote kg/ha), and the actuarial-fair premium rates for each crop. The results showed that, at different levels of coverage (i.e., from 50% to 90%), the actuarial-fair premium rates range between 0% and 32% of the sum assured. However, the range for cashew nuts is narrow (0% to 8%) while that of cotton is 4% to 32%, a very wider range compared to cashew nuts. Further, the expected losses for cotton, in the same coverage intervals, ranges from 11.58kg/ha to 256.06kg/ha while that of cashew was 0.44kg/ha to 19.69kg/ha.
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    Repetitive sampling inspection plan for cancer patients using exponentiated half-logistic distribution under indeterminacy
    (Springer Science and Business Media LLC, 2023) Rao, Gadde Srinivasa; Kirigiti, Peter Josephat
    This piece of work deals with a time truncated sampling scheme for cancer patients using exponentiated half-logistic distribution (EHLD) based on indeterminacy. We have studied time truncated schemes like repetitive acceptance sampling plan (RASP) under indeterminacy. We have estimated the projected scheme parameters such as sample size and acceptance and rejection sample numbers for known indeterminacy parameters. In addition to the projected sampling scheme quantities, the corresponding tables are generated for various values of indeterminacy parameters. The results of a sampling scheme show that the average sample number (ASN) decreases as indeterminacy values increase. It leads that the indeterminacy parameter is played a crucial portrayal in ASN. A comparative study is carried out with existing sampling schemes based on indeterminacy and classical sampling schemes. The evaluated sampling schemes are exemplified with the help of cancer data. From tables and exemplification, we wind up that the projected RSP scheme under indeterminacy desired a smaller sample size than the existing schemes.