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Estimation of Finite Population Totals in High Dimensional Spaces

Open Journal of Statistics 2022年第5期12卷 581-596页

作者： festus A. were George O. Orwa Romanus O. Otieno Department of Statistics and Actuarial Sciences JKUAT Nairobi Kenya

In this paper, the problem of Nonparametric Estimation of Finite Population Totals in high dimensional datasets is considered. A robust estimator of the Finite Population Total based on Feedforward Backpropagation Neural Network is derived with the aid of a Super-Population Model. This current study is motivated by the fact that Local Polynomials and Kernel methods have in preceding related studies, been shown to provide good estimators for Finite Population Totals but in low dimensions. Even in these situations however, bias at boundary points presents a big challenge when using these estimators in estimating Finite Population parameters. The challenge worsens as the dimension of regressors increase. This is because as the dimension of the Regressor Vectors grows, the Sparseness of the Regressors’ values in the design space becomes unfeasible, resulting in a decrease in the fastest achievable rates of convergence of the Regression Function Estimators towards the target curve, rendering Kernel Methods and Local Polynomials ineffective to address these challenges. This study considers the technique of Artificial Neural Networks which yields robust estimators in high dimensions and reduces the estimation bias with marginal increase in variance. This is due to its Multi-Layer Structure, which can approximate a wide range of functions to any required level of precision. The estimator’s properties are developed, and a comparison with existing estimators was conducted to evaluate the estimator’s performance using real data sets acquired from the United Nations Development Programme 2020. The estimation approach performs well in an example using data from a United Nations Development Programme 2020 on the study of Human Development Index against other factors. The theoretical and practical results imply that the Neural Network estimator is highly recommended for survey sampling estimation of the finite population total.

关键词： Neural Networks Kernel Smoother Local Polynomial Nonparametric

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Bias Correction Technique for Estimating Quantiles of Finite Populations under Simple Random Sampling without Replacement

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Open Journal of Statistics 2021年第5期11卷 854-869页

作者： Nicholas Makumi Romanus Odhiambo Otieno George Otieno Orwa festus were Habineza Alexis Pan African University Institute for Basic Sciences Technology and Innovation Nairobi Kenya Department of Mathematics Meru University of Science and Technology Meru Kenya Department of Statistics and Actuarial Sciences JKUAT Nairobi Kenya

In this paper, the problem of nonparametric estimation of finite population quantile function using multiplicative bias correction technique is considered. A robust estimator of the finite population quantile function based on multiplicative bias correction is derived with the aid of a super population model. Most studies have concentrated on kernel smoothers in the estimation of regression functions. This technique has also been applied to various methods of non-parametric estimation of the finite population quantile already under review. A major problem with the use of nonparametric kernel-based regression over a finite interval, such as the estimation of finite population quantities, is bias at boundary points. By correcting the boundary problems associated with previous model-based estimators, the multiplicative bias corrected estimator produced better results in estimating the finite population quantile function. Furthermore, the asymptotic behavior of the proposed estimators is presented. It is observed that the estimator is asymptotically unbiased and statistically consistent when certain conditions are satisfied. The simulation results show that the suggested estimator is quite well in terms of relative bias, mean squared error, and relative root mean error. As a result, the multiplicative bias corrected estimator is strongly suggested for survey sampling estimation of the finite population quantile function.

关键词： Quantile Function Kernel Estimator Multiplicative Bias Correction Technique Simple Random Sampling without Replacement

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Robust Classification through a Nonparametric Kernel Discriminant Analysis

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Open Journal of Statistics 2022年第4期12卷 443-455页

作者： Macdonald G. Obudho George O. Orwa Romanus O. Otieno festus A. were Department of Statistics and Actuarial Sciences Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya

The problem of classification in situations where the assumption of normality in the data is violated, and there are non-linear clustered structures in the dataset is addressed. A robust nonparametric kernel discriminant classification function, which is able to address this challenge, has been developed and the misclassification rates computed for various bandwidth matrices. A comparison with existing parametric classification functions such as the linear discriminant and quadratic discriminant is conducted to evaluate the performance of this classification function using simulated datasets. The results presented in this paper show good performance in terms of misclassification rates for the kernel discriminant classifier when the correct bandwidth is selected as compared to other identified existing classifiers. In this regard, the study recommends the use of the proposed kernel discriminant classification rule when one wishes to classify units into one of several categories or population groups where parametric classifiers might not be applicable.

关键词： Discriminant Analysis Kernel Discriminant Nonparametric

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Classification of Stateless People through a Robust Nonparametric Kernel Discriminant Function

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Open Journal of Statistics 2022年第5期12卷 563-580页

作者： Macdonald G. Obudho George O. Orwa Romanus O. Otieno festus A. were Department of Statistics and Actuarial Sciences Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya

Statelessness is the absence of any Nationality. These include the Pemba, Shona, Galjeel, people of Burundi and Rwanda descent, and children born in Kenya to British Overseas Citizens after 1983. Frequently, they are not only undocumented but also often overlooked and not included in National Administrative Registers. Accordingly, find it hard to participate in Social and Economic Affairs. There has been a major push by UNHCR and international partners to “map” the size of stateless populations and their demographic profile, as well as causes, potential solutions and human rights situation. One of the requirements by the UNHCR in their push is for countries to find a potential solution to statelessness which starts with classifying/associating a person from these communities to a particular local community that is recognized in Kenya. This paper addresses this problem by adopting a Robust Nonparametric Kernel Discriminant function to correctly classify the stateless communities in Kenya and compare the performance of this method with the existing techniques through their classification rates. This is because Non-parametric functions have proven to be more robust and useful especially when there exists auxiliary information which can be used to increase precision. The findings from this paper indicate that Nonparametric discriminant classifiers provide a good classification method for classifying the stateless communities in Kenya. This is because they exhibit lower classification rates compared to the parametric methods such as Linear and Quadratic discriminant functions. In addition, the finding shows that based on certain similarities in characteristics that exist in these communities that surround the Pemba Community, the Pemba community can be classified as Giriama or Rabai in which they seem to have a strong link. In this regard, the study recommends the use of the Kernel discriminant classifiers in classifying the stateless persons and that the Government of K

关键词： Discriminant Analysis Kernel Discriminant Nonparametric Classification Statelessness

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Distribution, health and ecological risk assessments of trace elements in Nigerian oil sands

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Acta Geochimica 2024年第1期43卷 59-71页

作者： Odunayo T.Ore festus M.Adebiyi Department of Chemistry Obafemi Awolowo UniversityIle-Ife 220005Nigeria Department of Chemical Sciences Achievers UniversityOwoNigeria

The Nigerian oil sands represent the largest oil sand deposit in Africa, yet there is little published information on the distribution and potential health and ecological risks of trace elements in the oil resource. In the present study, we investigated the distribution pattern of 18trace elements(including biophile and chalcophile elements) as well as the estimated risks associated with exposure to these elements. The results of the study indicated that Fe was the most abundant element, with a mean concentration of 22,131 mg/kg while Br had the lowest mean concentration of 48 mg/kg. The high occurrence of Fe and Ti suggested a possible occurrence of ilmenite(Fe TiO_(3)) in the oil sands. Source apportionment using positive matrix factorization showed that the possible sources of detected elements in the oil sands were geogenic, metal production, and crustal. The contamination factor, geo-accumulation index, modified degree of contamination, pollution load index, and Nemerow pollution index indicated that the oil sands are heavily polluted by the elements. Health risk assessment showed that children were relatively more susceptible to the potentially toxic elements in the oil sands principally via ingestion exposure route(HQ > 1E-04). Cancer risks from inhalation are unlikely due to CR 1E-04). The high concentrations of the elements pose serious threats due to the potential for atmospheric transport, bioaccessibility, and bioavailability.

关键词： Biophile Chalcophile Oil sand Risk assessment Trace element

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Impact of Large Language Models on Scholarly Publication Titles and Abstracts:A Comparative Analysis

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Journal of Social Computing 2024年第2期5卷 105-121页

作者： Phoey Lee Teh Chukwudi festus Uwasomba the Department of Cyber and Computing Wrexham UniversityWrexhamLL112AWUK the School of Computing and Computing STEM FacultyThe Open UniversityMilton KeynesMK76AAUK

Artificial Intelligence(AI)tools become essential across industries,distinguishing AI-generated from human-authored text is increasingly *** study assesses the coherence of AI-generated titles and corresponding abstracts in anticipation of rising AI-assisted document *** main goal is to examine the correlation between original and AI-generated titles,emphasizing semantic depth and similarity measures,particularly in the context of Large Language Models(LLMs).We argue that LLMs have transformed research focus,dissemination,and citation patterns across five selected knowledge areas:Business Administration and Management(BAM),Computer Science and Information Technology(CS),Engineering and Material Science(EMS),Medicine and Healthcare(MH),and Psychology and Behavioral Sciences(PBS).We collected 15000 titles and abstracts,narrowing the selection to 2000 through a rigorous multi-stage screening process adhering to our study’s *** shows that there is insufficient evidence to suggest that LLM outperforms human authors in article title generation or articles from the LLM era demonstrates a marked difference in semantic richness and readability compared to those from the ***,it asserts that LLM is a valuable tool and can assist researchers in generating *** LLM’s assistance,the researcher ensures that the content is reflective of the finalized abstract and core research themes,potentially increasing the impact and accessibility and readability of the academic work.

关键词： semantic alignment cosine similarity patterns large language models technology impact

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Innuendoes of Sterilisation Drilling in Surface Mining Operations—A Case Study

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International Journal of Geosciences 2024年第5期15卷 458-477页

作者： Richard Gyebuni festus Kunkyin-Saadaari Isaac Ekow Anaman Department of Mining Engineering University of Mine and Technology Tarkwa Ghana Mining Engineering Department Ghana Manganese Company Tarkwa Ghana

Surface mining operations play a crucial role in meeting the world’s increasing demand for mineral resources for the advancement of technology and debauched expansion of economies. The search for and exploitation of these mineral resources are therefore important for the sustainability of the mineral extraction industry. To this end, efficient mine planning must incorporate sterilisation drilling and effective waste rock management principles in the search and exploitation of these minerals. In this article, sterilisation drilling is being reviewed vis-a-vis the establishment of waste and tailings dump locations, backfilling of open pit excavations and mine closure giving critical attention to the minerals and mining laws of Ghana. Subsequently, a detailed case study of a surface mining operation that successfully incorporated sterilisation drilling in determining waste dump location in its mine planning process has been presented in this study. The findings indicate that the proposed waste dump location could present a potential mining prospect in the future based on enhanced milling capacity/technology and improved mineral commodity price;underscoring the significance of sterilization drilling in the sustainability of the mining industry.

关键词： Sterilisation Exploration Backfilling Waste Dump Cutoff Grade

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Innuendoes of Sterilisation Drilling in Surface Mining Operations—A Case Study

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International Journal of Geosciences（地球科学国际期刊） 2024年第5期15卷 458页

Surface mining operations play a crucial role in meeting the world’s increasing demand for mineral resources for the advancement of technology and debauched expansion of economies. The search for and exploitation of these mineral resources are therefore important for the sustainability of the mineral extraction industry. To this end, efficient mine planning must incorporate sterilisation drilling and effective waste rock management principles in the search and exploitation of these minerals. In this article, sterilisation drilling is being reviewed vis-a-vis the establishment of waste and tailings dump locations, backfilling of open pit excavations and mine closure giving critical attention to the minerals and mining laws of Ghana. Subsequently, a detailed case study of a surface mining operation that successfully incorporated sterilisation drilling in determining waste dump location in its mine planning process has been presented in this study. The findings indicate that the proposed waste dump location could present a potential mining prospect in the future based on enhanced milling capacity/technology and improved mineral commodity price; underscoring the significance of sterilization drilling in the sustainability of the mining industry.

关键词： Sterilisation Exploration Backfilling Waste Dump Cutoff Grade

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Exploring a New Lifetime Distribution for Modelling the Waiting Time of Bank Customers

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Journal of Applied Mathematics and Physics 2024年第1期12卷 194-209页

作者： Simon A. Ogumeyo Jacob C. Ehiwario festus C. Opone Department of Mathematics Delta State University of Science and Technology Ozoro Nigeria Department of Statistics University of Delta Agbor Nigeria Department of Statistics Delta State University of Science and Technology Ozoro Nigeria

The fitting of lifetime distribution in real-life data has been studied in various fields of research. With the theory of evolution still applicable, more complex data from real-world scenarios will continue to emerge. Despite this, many researchers have made commendable efforts to develop new lifetime distributions that can fit this complex data. In this paper, we utilized the KM-transformation technique to increase the flexibility of the power Lindley distribution, resulting in the Kavya-Manoharan Power Lindley (KMPL) distribution. We study the mathematical treatments of the KMPL distribution in detail and adapt the widely used method of maximum likelihood to estimate the unknown parameters of the KMPL distribution. We carry out a Monte Carlo simulation study to investigate the performance of the Maximum Likelihood Estimates (MLEs) of the parameters of the KMPL distribution. To demonstrate the effectiveness of the KMPL distribution for data fitting, we use a real dataset comprising the waiting time of 100 bank customers. We compare the KMPL distribution with other models that are extensions of the power Lindley distribution. Based on some statistical model selection criteria, the summary results of the analysis were in favor of the KMPL distribution. We further investigate the density fit and probability-probability (p-p) plots to validate the superiority of the KMPL distribution over the competing distributions for fitting the waiting time dataset.

关键词： KM-Transformation Power Lindley Distribution Data Fitting Moments Quantiles

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Investigation of Groundwater Quality with Borehole Depth in the Basin Granitoids of the Ashanti Region of Ghana

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Journal of Water Resource and Protection 2024年第5期16卷 381-394页

作者： Bernard Ofosu Augustine Kofi Asante festus Anane Mensah Umar-Farouk Usman Naa Korkoi Ayeh Geotechnical and Materials Engineering Division CSIR-Building and Road Research Institute Kumasi Ghana

The dependence of groundwater quality on borehole depth is usually debatable in groundwater studies, especially in complex geological formations where aquifer characteristics vary spatially with depth. This study therefore seeks to investigate the relationship between borehole depth and groundwater quality across the granitoid aquifers within the Birimian Supergroup in the Ashanti Region. Physicochemical analysis records of groundwater quality data were collected from 23 boreholes of public and private institutions in the Ashanti Region of Ghana, and the parametric values of iron, fluoride, total hardness, pH, nitrate, and nitrite were used to study the groundwater quality-depth relationship. The results showed that the depth-to-groundwater quality indicated a marginal increase in water quality in the range of 30 to 50 m, which is mathematically represented by the low-value correlation coefficient (r2 = 0.026). A relatively significant increase occurs in the depth range of 50 to 80 m, which is given by a correlation coefficient of r2 = 0.298. The mean percent parameter compatibility was 74%, 82%, 89%, and 97% at 50, 60, 70, and 80 m depths, respectively. The variations in groundwater quality per depth ratio ranged from 1.48, 1.37, 1.27, and 1.21 for 50, 60, 70, and 80 m depth, respectively. The recommended minimum borehole depth for excellent groundwater quality is suggested with a compatibility per meter depth ratio of 1.37. This results in a range between 50 and 70 m as the most desirable drilling depth for excellent groundwater quality within the granitoids of the Birimian Supergroup of the Ashanti Region in Ghana.

关键词： Groundwater Quality Borehole Depth Birimian Supergroup Granitoid Aquifers Ashanti Region

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