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Research Article
Lifetime Distribution Based on Generators for Discrete Mixtures with Application to Lomax Distribution
Peter Nyandiri Mecha,
Isaac Chumba Kipchirchir,
George Odweso Muhua,
Joseph Antony Makoteku Ottieno
Issue:
Volume 14, Issue 2, April 2025
Pages:
51-60
Received:
15 July 2024
Accepted:
24 December 2024
Published:
13 March 2025
DOI:
10.11648/j.ajtas.20251402.11
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Abstract: In various application areas, data is frequently collected and analyzed using basic statistical distributions such as exponential, Poisson, and gamma distributions. However, these traditional distributions often fail to adequately capture the inherent heterogeneity present in real-world data. This limitation highlights the need for more flexible distributions that can address these complexities. Such distributions can be generated through techniques like reparameterization, generalization, compounding, and mixing. This paper focuses on deriving generators for survival functions of discrete mixtures using minimum and maximum order statistic distributions. The approach leverages the probability generating function (PGF) techniques of mixing distributions, including zero-truncated Poisson, shifted geometric, zero-truncated binomial, zero-truncated negative binomial, and logarithmic series distributions. Specifically, the derived generator was applied to Lomax distributions to construct survival functions. Consequently, the probability density function (PDF) and failure rate of the resulting discrete mixtures were also obtained. Furthermore, the paper examines the shapes of the PDF and failure rate for discrete mixtures derived from the zero-truncated Poisson distribution. Notably, the failure rates of discrete mixtures generated using minimum and maximum order statistics from the Lomax distribution exhibited distinct behaviors. The failure rate for the minimum order statistic was observed to decrease, while the failure rate for the maximum order statistic showed a combination of non-decreasing and bathtub-shaped patterns.
Abstract: In various application areas, data is frequently collected and analyzed using basic statistical distributions such as exponential, Poisson, and gamma distributions. However, these traditional distributions often fail to adequately capture the inherent heterogeneity present in real-world data. This limitation highlights the need for more flexible di...
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Research Article
Study on Efficacy of Kendall’s τ Based Test Statistic in Generalized Partially Linear Regression Model
Issue:
Volume 14, Issue 2, April 2025
Pages:
61-76
Received:
12 February 2025
Accepted:
3 March 2025
Published:
24 March 2025
Abstract: Under the setup of a generalized partially linear model Y = β1X1+ ... + βpXp+ m(W1,...,Wq) + ϵ with p parametric regressors X1,..., Xp and q nonparametric regressors W1,..., Wq, we are motivated to test on the independence between all the (p + q) regressors and the random error ϵ. Since one obtains unbiased prediction of the study variable of interest when the regressors under consideration are independent of the random error, such testing of independence is a vital objective indeed. Here, m(W1,..., Wq) is a Lipschitz continuous function defined on ℝq→ℝ. To carry out the prescribed testing scheme, some test statistics are formed based on the nonparametric measure of association Kendall’s (1938) τ. Moreover, as an implication of the null hypothesis suggesting independence between joint (p + q) regressors and ϵ, we further modify the hypothesis as ϵ is not observable at all. Eventually, independence among the r-th order difference of estimated response and the r-th order difference of observed response is implied from the original null hypothesis. Later, the concept of V-statistic is applied to propose the test statistics based on the paired observations on the r-th differences of the estimated and observed Y. Their consistent power performances are achieved under a sequence of contiguous alternatives stating complete dependence between error and regressors while testing the independence of regressors with ϵ. Le Cam (1960)’s theory on contiguity is required to develop a sequence of contiguous alternative hypotheses in this regard. The asymptotic powers of the test statistics are evaluated with the help of their asymptotic distributions under null hypothesis of independence and contiguous alternatives. Subsequently, a data analysis is performed to substantiate the eligibility of the proposed test statistics in such testing setup.
Abstract: Under the setup of a generalized partially linear model Y = β1X1+ ... + βpXp+ m(W1,...,Wq) + ϵ with p parametric regressors X1,..., Xp and q nonparametric regressors W1,..., Wq, we are motivated to test on the independence between all the (p + q) regressors and the random error ϵ. Since one obtains unbiased prediction of the study variable of inter...
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Research Article
Performance Evaluation of Small Scale Irrigation Scheme and Its Contribution to Household’s Food Security: A Case Study of Fitte, Wayu Tuka Woreda, East Wallaga Zone, Oromia, Ethiopia
Kuma Abebe*
,
Megersa Tesfaye,
Gemechu Mosisa,
Yadesa Wakena
Issue:
Volume 14, Issue 2, April 2025
Pages:
77-88
Received:
18 November 2024
Accepted:
24 December 2024
Published:
31 March 2025
Abstract: Performance evaluation is an important aspect of assessing the success of irrigation management. The Fitte Small-Scale irrigation was used as a case study in this research to evaluate the performance of the small-scale irrigation scheme and its contribution to household food security. The study used a variety of irrigation performance indicators, such as physical, major output, and water consumption (input-related) indicators, to evaluate the schemes performance and develop a feasible water distribution system to satisfy the populations growing food needs. The study was initiated at the beginning of the irrigation season in January 2022. To achieve its objectives, the study utilized primary and secondary data that were collected and analysed. It was reported that CROPWAT 8.0, GIS, Climwat2 software, and statistical tools were utilized to carry out data analysis and manipulation tasks. A variety of performance indicator categories, such as water use, physical outputs, and agricultural outputs, were then used to assess the plan. The findings showed that the Fitte system had an irrigation supply value of 3.9 and a relative water supply value of 3.2. This demonstrates that the irrigation area may be increased by making better use of water because it shows that more water was supplied than was required. In terms of physical indicators, the irrigation ratio was 0.58, and the sustainability of the irrigated area was 0.7. The Fitte scheme's output per unit of water provided, output per unit of irrigation diverted water, output per unit of cropped area, and output per command area were 110,610.7 birr/ha, 129,045.8 birr/ha, 6.8 birr/ha, and 7.8 birr/ha, respectively, according to the analysis. The results show that the Fitte system did not perform well. It is important to remember that the area under irrigation was smaller than the planned command area. The study's findings demonstrate that irrigation improves agriculture by increasing output and productivity, which in turn enhances asset development and food security.
Abstract: Performance evaluation is an important aspect of assessing the success of irrigation management. The Fitte Small-Scale irrigation was used as a case study in this research to evaluate the performance of the small-scale irrigation scheme and its contribution to household food security. The study used a variety of irrigation performance indicators, s...
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Research Article
Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model
Abdirashid Mohamed Hussein*,
Ahmed Hassan Abdillahi
Issue:
Volume 14, Issue 2, April 2025
Pages:
89-98
Received:
25 March 2025
Accepted:
2 April 2025
Published:
29 April 2025
DOI:
10.11648/j.ajtas.20251402.14
Downloads:
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Abstract: This study examines the modeling and forecasting of Somalia’s Consumer Price Index (CPI) using the ARIMA model, with data from November 2022 to November 2024. Descriptive analysis reveals a mean CPI of 144.26, moderate variability, and a slight negative skew. The CPI series is unstable in its original form but achieves stability after first differencing. The ARIMA (1,1,0) model is selected as the best fit, based on its low AIC and BIC values, with diagnostic checks confirming its effectiveness in capturing the data patterns. Forecasts suggest a stable CPI of approximately 152.95 from December 2024 to November 2026, though prediction intervals widen over time, reflecting increased uncertainty. The model performs well, with a Mean Absolute Percentage Error (MAPE) of 6.18%, though slight underestimation bias is noted. These findings demonstrate that ARIMA forecasts can aid policymakers in designing effective inflation control measures in volatile economies. These insights can help the Central Bank and policymakers implement timely interventions to stabilize prices and manage inflation expectations. Future research should incorporate external economic factors for more robust long-term predictions.
Abstract: This study examines the modeling and forecasting of Somalia’s Consumer Price Index (CPI) using the ARIMA model, with data from November 2022 to November 2024. Descriptive analysis reveals a mean CPI of 144.26, moderate variability, and a slight negative skew. The CPI series is unstable in its original form but achieves stability after first differe...
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