Pub Date : 2024-04-19DOI: 10.9734/ajpas/2024/v26i4607
Bahadır Yılmaz, Y. Soykan
In this study, we investigate the generalized dual hyperbolic Guglielmo numbers and then various special cases are explored (including dual triangular numbers, dual triangular-Lucas numbers, dual oblong numbers, and dual pentagonal numbers). Binet's formulas, generating functions, and summation formulas for these numbers are presented. Additionally, Catalan's and Cassini's identities are provided, along with matrices associated with these sequences. Moreover, we give some identities and matrices related with these sequences.
{"title":"An Analytical Study on Dual Generalized Guglielmo Numbers","authors":"Bahadır Yılmaz, Y. Soykan","doi":"10.9734/ajpas/2024/v26i4607","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i4607","url":null,"abstract":"In this study, we investigate the generalized dual hyperbolic Guglielmo numbers and then various special cases are explored (including dual triangular numbers, dual triangular-Lucas numbers, dual oblong numbers, and dual pentagonal numbers). Binet's formulas, generating functions, and summation formulas for these numbers are presented. Additionally, Catalan's and Cassini's identities are provided, along with matrices associated with these sequences. Moreover, we give some identities and matrices related with these sequences.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140684393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-17DOI: 10.9734/ajpas/2024/v26i4606
Juan Carlos Rosales, Betina Abad
Aims/ Objectives:: In this work we describe the first historical Zika virus outbreak recorded in Salta, Argentina, in the year 2017, through Monte Carlo-type simulations using the Poisson model. Later we made comparisons with previous results.Study Design: Retrospective-descriptive studies and stochastic computational experiment analysis Place and Duration of Study: Department of Mathematic, Faculty of Exact Sciences. National University of Salta, Argentina, from March 2021 to December 2023.Methodology: Descriptive and computational experiment analysis. Parameter estimation by Maximum Likelihood and Simulation of type Monte Carlo.Results: We describe the probabilistic behavior through Monte Carlo simulations of the first historical outbreak of Zika in Salta Argentina, 2017. Based on the data of registered Zika cases, we estimate a probabilistic Poisson model with parameter(hat{lambda}) = 13:092 casesweek-1 and confidence interval 95%CI [11:889- 15:110]. Finally, by computational experiments we generate epidemic outbreaks with 20 runs. The computational experiments shows that, from a qualitative point of view, the descriptions of the outbreak are qualitatively acceptable and they were not better than the probabilistic model obtained in a previous study. However, from the statistical point of view, carrying out computational experiments of 10 comparative runs in each model, the models provide simulations of epidemic outbreaks by Zika virus, for this region of Salta, Argentina, that do not differ significantly at a confidence level of 5%.
{"title":"Modelling by Generation of Poisson Distributed Numbers of First Historical Zika Outbreak in Salta, Argentina","authors":"Juan Carlos Rosales, Betina Abad","doi":"10.9734/ajpas/2024/v26i4606","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i4606","url":null,"abstract":"Aims/ Objectives:: In this work we describe the first historical Zika virus outbreak recorded in Salta, Argentina, in the year 2017, through Monte Carlo-type simulations using the Poisson model. Later we made comparisons with previous results.Study Design: Retrospective-descriptive studies and stochastic computational experiment analysis Place and Duration of Study: Department of Mathematic, Faculty of Exact Sciences. National University of Salta, Argentina, from March 2021 to December 2023.Methodology: Descriptive and computational experiment analysis. Parameter estimation by Maximum Likelihood and Simulation of type Monte Carlo.Results: We describe the probabilistic behavior through Monte Carlo simulations of the first historical outbreak of Zika in Salta Argentina, 2017. Based on the data of registered Zika cases, we estimate a probabilistic Poisson model with parameter(hat{lambda}) = 13:092 casesweek-1 and confidence interval 95%CI [11:889- 15:110]. Finally, by computational experiments we generate epidemic outbreaks with 20 runs. The computational experiments shows that, from a qualitative point of view, the descriptions of the outbreak are qualitatively acceptable and they were not better than the probabilistic model obtained in a previous study. However, from the statistical point of view, carrying out computational experiments of 10 comparative runs in each model, the models provide simulations of epidemic outbreaks by Zika virus, for this region of Salta, Argentina, that do not differ significantly at a confidence level of 5%.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"17 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140694085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-13DOI: 10.9734/ajpas/2024/v26i4605
Saheed A. Afolabi
Population census supplies a complete and accurate picture of a country's population and its residents' characteristics. Modeling population growth has been worked upon by different scholars before now with more of a classical approach and less of a Bayesian approach. Therefore, an attempt is made in this work to apply Bayesian probabilistic projection on the usual exponential growth rate model in estimating population parameters and predicting population census in the Kingdom of Saudi Arabia (KSA) across thirteen (13) regions. The obtained data from WorldData and United Nations Population were used for the estimation and projection with the application of appropriate prior, likelihood, and posterior selection through Bayesian inference. This approach is reasonably accurate and well-calibrated with a significant precision of 0.01025 approximately 99% model accuracy for the period due to the estimated population parameters that were used: to make a comparison with the 2019 Population Census of Saudi Arabia which was perfectly closed and to forecast for the next 80 years using out-sample cases.
{"title":"Bayesian Probabilistic Projection of Population Census in the Kingdom of Saudi Arabia","authors":"Saheed A. Afolabi","doi":"10.9734/ajpas/2024/v26i4605","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i4605","url":null,"abstract":"Population census supplies a complete and accurate picture of a country's population and its residents' characteristics. Modeling population growth has been worked upon by different scholars before now with more of a classical approach and less of a Bayesian approach. Therefore, an attempt is made in this work to apply Bayesian probabilistic projection on the usual exponential growth rate model in estimating population parameters and predicting population census in the Kingdom of Saudi Arabia (KSA) across thirteen (13) regions. The obtained data from WorldData and United Nations Population were used for the estimation and projection with the application of appropriate prior, likelihood, and posterior selection through Bayesian inference. This approach is reasonably accurate and well-calibrated with a significant precision of 0.01025 approximately 99% model accuracy for the period due to the estimated population parameters that were used: to make a comparison with the 2019 Population Census of Saudi Arabia which was perfectly closed and to forecast for the next 80 years using out-sample cases.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"9 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140707339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-08DOI: 10.9734/ajpas/2024/v26i4604
Cailing Li
The note considers a risk model with dependence and capital injections, where the dependence structure is modeled by a Farlie-Gumbel-Morgenstern copula. In the risk model, the initial surplus starts from a level u (ge) h, where h > 0 is a fix constant. The author derives an expression for the Laplace transform of the Gerber-Shiu function. In particular, an explicit formula for the Gerber-Shiu function is obtained when the initial surplus is h.
本说明考虑了一个具有依赖性和注资的风险模型，其中依赖结构由 Farlie-Gumbel-Morgenstern copula 建模。在该风险模型中，初始盈余从一个水平 u （ge）h 开始，其中 h > 0 是一个固定常数。作者推导出了格伯-修函数的拉普拉斯变换表达式。特别是，当初始盈余为 h 时，可以得到格伯-修函数的明确公式。
{"title":"A Note on the Risk Model with Dependence and Capital Injections","authors":"Cailing Li","doi":"10.9734/ajpas/2024/v26i4604","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i4604","url":null,"abstract":"The note considers a risk model with dependence and capital injections, where the dependence structure is modeled by a Farlie-Gumbel-Morgenstern copula. In the risk model, the initial surplus starts from a level u (ge) h, where h > 0 is a fix constant. The author derives an expression for the Laplace transform of the Gerber-Shiu function. In particular, an explicit formula for the Gerber-Shiu function is obtained when the initial surplus is h.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"62 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140730196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.9734/ajpas/2024/v26i3603
Osamo Caleb Kehinde, O. Nwankwo, Awogbemi, Clement Adeyeye, Charles C. Okeke
Economic growth is a function of some productive efforts among which savings mobilizations is considered very vital. This study examines savings mobilization strategy and its impact on Nigeria’s economic growth during the year 2001-2022.This is vested with the objectives to investigate the effect of banking density, savings rates and money supply on economic growth. The study relies on time series data sourced from the publication of the Central Bank of Nigeria. Gross Domestic Product Growth Rate (GDPGR) was adopted as dependent variable, while Banking Density (BD), Savings Rates (SR) and Money Supply (MS) were the independent variables. Augmented Dickey Fuller (ADF) unit root test was employed, to test the stationarity. The Auto Regressive Distributive Lag (ADRL) was used to ascertain the relationship between the variables alongside Vector Error Correction Model (VCM). Post estimation diagnostic tools used include Breuch-Godfrey serial correlation LM test and the CUSUM test for stability. From the ARDL, β-coefficient and the associated probabilities were adopted to determine the extent and direction of relationship on economic growth. Data were tested at 5% level of significance; it was discovered that banking density and savings rates affected economic growth positively but with insignificant effects, while money supply affected economic growth negatively with insignificant effect. The study therefore recommends amongst others, that stakeholders, be directed towards entrenching higher banking density as opposed to banking desert, and that money supply should be made dynamic in accordance with economic realities.
{"title":"Analysis of the Effects of Money Market Fund Mobilization on the Dynamics of Nigerian Economic Growth","authors":"Osamo Caleb Kehinde, O. Nwankwo, Awogbemi, Clement Adeyeye, Charles C. Okeke","doi":"10.9734/ajpas/2024/v26i3603","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i3603","url":null,"abstract":"Economic growth is a function of some productive efforts among which savings mobilizations is considered very vital. This study examines savings mobilization strategy and its impact on Nigeria’s economic growth during the year 2001-2022.This is vested with the objectives to investigate the effect of banking density, savings rates and money supply on economic growth. The study relies on time series data sourced from the publication of the Central Bank of Nigeria. Gross Domestic Product Growth Rate (GDPGR) was adopted as dependent variable, while Banking Density (BD), Savings Rates (SR) and Money Supply (MS) were the independent variables. Augmented Dickey Fuller (ADF) unit root test was employed, to test the stationarity. The Auto Regressive Distributive Lag (ADRL) was used to ascertain the relationship between the variables alongside Vector Error Correction Model (VCM). Post estimation diagnostic tools used include Breuch-Godfrey serial correlation LM test and the CUSUM test for stability. From the ARDL, β-coefficient and the associated probabilities were adopted to determine the extent and direction of relationship on economic growth. Data were tested at 5% level of significance; it was discovered that banking density and savings rates affected economic growth positively but with insignificant effects, while money supply affected economic growth negatively with insignificant effect. The study therefore recommends amongst others, that stakeholders, be directed towards entrenching higher banking density as opposed to banking desert, and that money supply should be made dynamic in accordance with economic realities.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"50 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140735660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.9734/ajpas/2024/v26i3602
B. U., Igwe N. O.
This study examines the Socio-Economic and Demographic Factors that influence Contraceptive use by Married Men in Afikpo North Local Government Area of Ebonyi State. It is aimed at identifying the determinants of contraceptive use among married men in Afikpo North Local Government Area of Ebonyi State. A sample of four hundred and sixty one (461) married men were selected for the study through Multi-Stage sampling design. Cross tabulation results revealed that there is a significant relationship between the independent variables and contraceptive use. Logistic regression results showed that the significant socio-economic and demographic determinants of contraceptives use among the study sample are marriage duration of at least five years, religion, education, occupation, parity, number of children living and age. The Hosmer Lemeshow test for goodness of fit of the logistic regression model is 87.9 percent and is highly significant (p-value > 0.05). This indicates that the model fitted is adequate. The study recommends among others that it is necessary for young couples with less than five-year experience, Muslims, the no education group and farmers, to be targeted and carried along in the campaign for the use of contraceptive methods.
{"title":"Socio-Economic and Demographic Factors that Influence Contraceptive Use by Men in Afikpo North Local Government Area of Ebonyi State","authors":"B. U., Igwe N. O.","doi":"10.9734/ajpas/2024/v26i3602","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i3602","url":null,"abstract":"This study examines the Socio-Economic and Demographic Factors that influence Contraceptive use by Married Men in Afikpo North Local Government Area of Ebonyi State. It is aimed at identifying the determinants of contraceptive use among married men in Afikpo North Local Government Area of Ebonyi State. A sample of four hundred and sixty one (461) married men were selected for the study through Multi-Stage sampling design. Cross tabulation results revealed that there is a significant relationship between the independent variables and contraceptive use. Logistic regression results showed that the significant socio-economic and demographic determinants of contraceptives use among the study sample are marriage duration of at least five years, religion, education, occupation, parity, number of children living and age. The Hosmer Lemeshow test for goodness of fit of the logistic regression model is 87.9 percent and is highly significant (p-value > 0.05). This indicates that the model fitted is adequate. The study recommends among others that it is necessary for young couples with less than five-year experience, Muslims, the no education group and farmers, to be targeted and carried along in the campaign for the use of contraceptive methods.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"5 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140739090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-28DOI: 10.9734/ajpas/2024/v26i3601
Mohammed Idris Umar, M. U. Adehi, A. Auwal
Prolonged wait (queue) times in medical outpatient departments are a growing concern in Nigerian hospitals/clinics, due to a variety of consequences such as overcrowding, patients leaving in anger without being attended to, and being stressed for not staying too long in the system. The primary goal of this paper is to research various techniques or methods for reducing long queues. Patients who wait for minutes, hours, days, or months to receive medical services may incur waiting costs. The time spent in the queue could have been better used elsewhere. This paper aims to determine an optimal server level while keeping total system costs to a minimum, including expected service costs and waiting costs in a multi-server system, to reduce patient congestion in the hospital. Data for the study was collected in two ways. The secondary method was first used to identify the most congested OPD among the numerous OPDs considered in the study. The performance measures costs were then calculated using primary data. The performance measures of the queuing system were calculated using TORA optimization software. MS Excel was used to calculate the costs and plot the charts. Based on the results of the analysis, it was suggested that one physician be added to the hospital's medical OPD to reduce patient overcrowding and wait times. As a result, this call for refocusing is issued to improve overall patient care in our cultural context while also meeting the needs of patients in our society.
在尼日利亚的医院/诊所，医疗门诊部等候（排队）时间过长是一个日益令人担忧的问题，其原因有多种，如过度拥挤、病人因得不到诊治而愤然离去，以及因在系统中停留时间过长而感到压力等。本文的主要目的是研究减少排长队现象的各种技术或方法。患者等待几分钟、几小时、几天或几个月才能获得医疗服务，可能会产生等待成本。排队时间本可以更好地用于其他方面。本文旨在确定一个最佳服务器级别，同时将系统总成本（包括多服务器系统中的预期服务成本和等待成本）保持在最低水平，以减少医院中的病人拥堵现象。研究数据通过两种方式收集。首先使用辅助方法在研究中考虑的众多手术室中找出最拥挤的手术室。然后使用原始数据计算绩效衡量成本。使用 TORA 优化软件计算排队系统的性能指标。MS Excel 用于计算成本和绘制图表。根据分析结果，建议在医院内科手术室增加一名医生，以减少病人拥挤和等候时间。因此，我们呼吁调整工作重点，以便在我们的文化背景下改善对病人的整体护理，同时满足社会中病人的需求。
{"title":"An Investigation of Multi-server Queuing Analysis to Assess Hospital Healthcare Systems' Operational Effectiveness","authors":"Mohammed Idris Umar, M. U. Adehi, A. Auwal","doi":"10.9734/ajpas/2024/v26i3601","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i3601","url":null,"abstract":"Prolonged wait (queue) times in medical outpatient departments are a growing concern in Nigerian hospitals/clinics, due to a variety of consequences such as overcrowding, patients leaving in anger without being attended to, and being stressed for not staying too long in the system. The primary goal of this paper is to research various techniques or methods for reducing long queues. Patients who wait for minutes, hours, days, or months to receive medical services may incur waiting costs. The time spent in the queue could have been better used elsewhere. This paper aims to determine an optimal server level while keeping total system costs to a minimum, including expected service costs and waiting costs in a multi-server system, to reduce patient congestion in the hospital. Data for the study was collected in two ways. The secondary method was first used to identify the most congested OPD among the numerous OPDs considered in the study. The performance measures costs were then calculated using primary data. The performance measures of the queuing system were calculated using TORA optimization software. MS Excel was used to calculate the costs and plot the charts. Based on the results of the analysis, it was suggested that one physician be added to the hospital's medical OPD to reduce patient overcrowding and wait times. As a result, this call for refocusing is issued to improve overall patient care in our cultural context while also meeting the needs of patients in our society.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"28 28","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140373038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-29DOI: 10.9734/ajpas/2024/v26i3596
Jane Wangui Runo, A. Anapapa, E. Nyarige
According to the World Bank (2022), approximately 8.9 million people, or 17% of Kenya’s population, live below the poverty line of 1.9 USD on a daily basis, majority of them in the rural areas. This research aimed to analyze the impact of self-help groups on the livelihoods of rural areas of Kenya, with the goal of promoting sustainable livelihoods and reducing poverty. To achieve this, the study employed machine learning specifically the logistic regression algorithm to model the impact of self-help groups on livelihoods in Murang’a East sub-county. The study used primary data obtained through the issuance of structured questionnaires to SHG members, on their wealth status since joining the self-help groups on areas such as ability to save, access to credit services and acquiring assets, both income generating and household. A total of 969 members of self-help groups were issued with the questionnaire. The study’s findings helped identify the key predictors of members’ livelihoods and provided insights into how self-help groups influence them. The results of logistic regression indicated that 91.33% of the members had seen a significant improvement on their wealth status since joining self-help groups and the significant predictor variables were income generating assets, access to basic commodities and access to loans. The model’s accuracy was 88.04%. The ethical considerations in this study included ensuring no coercion or pressure to participate in the study and confidentiality and privacy of the respondents.
{"title":"Modeling Self Help Groups’ Impact on Livelihoods in Murang’a East Sub-County: A Logistic Regression Approach","authors":"Jane Wangui Runo, A. Anapapa, E. Nyarige","doi":"10.9734/ajpas/2024/v26i3596","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i3596","url":null,"abstract":"According to the World Bank (2022), approximately 8.9 million people, or 17% of Kenya’s population, live below the poverty line of 1.9 USD on a daily basis, majority of them in the rural areas. This research aimed to analyze the impact of self-help groups on the livelihoods of rural areas of Kenya, with the goal of promoting sustainable livelihoods and reducing poverty. To achieve this, the study employed machine learning specifically the logistic regression algorithm to model the impact of self-help groups on livelihoods in Murang’a East sub-county. The study used primary data obtained through the issuance of structured questionnaires to SHG members, on their wealth status since joining the self-help groups on areas such as ability to save, access to credit services and acquiring assets, both income generating and household. A total of 969 members of self-help groups were issued with the questionnaire. The study’s findings helped identify the key predictors of members’ livelihoods and provided insights into how self-help groups influence them. The results of logistic regression indicated that 91.33% of the members had seen a significant improvement on their wealth status since joining self-help groups and the significant predictor variables were income generating assets, access to basic commodities and access to loans. The model’s accuracy was 88.04%. The ethical considerations in this study included ensuring no coercion or pressure to participate in the study and confidentiality and privacy of the respondents.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"27 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140409151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-29DOI: 10.9734/ajpas/2024/v26i2595
Wahome Muthoni Loise, John W. Mutuguta, E. Nyarige
Around the world, depression is a prevalent mental illness and it affects the way people think, feel, talk and conduct their daily activities. The associated stigma often leads to misdiagnosis, posing risks such as disability and suicide. The study employed random forest algorithm to model the prevalence of depression among Murang’a University of technology (MUT) students. A sample of 1448 students from the different schools at the university participated in the study by completing questionnaires on sociodemographic and other factors associated with depression. The questionnaires were administered through social media platforms. Participants were selected using proportionate stratified random sampling and simple random sampling to ensure that a representative sample was chosen from each school. The data gathered was examined using descriptive and inferential statistics. Depression was measured using the Patient Health Questionnaire scale (PHQ-9). Using a cut-off point of 10, 25.97% students had depressive symptoms. This comprised of 19.61% moderate symptoms and 6.35% severe symptoms. The confusion matrix criteria were used to assess the performance of random forest in modeling depression prevalence among MUT students. Metrics for random forest included, accuracy (0.9868), sensitivity (0.95), specificity (1.00), positive predictive value (1.00), and negative predictive value (0.9824). Implementing targeted interventions founded on identified risk and protective factors and exploring the long-term outcomes of these interventions would contribute to the evolving field of mental health research within academic settings.
{"title":"Application of Random Forest in Modeling the Prevalence of Depression among Murang’a University of Technology Students","authors":"Wahome Muthoni Loise, John W. Mutuguta, E. Nyarige","doi":"10.9734/ajpas/2024/v26i2595","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i2595","url":null,"abstract":"Around the world, depression is a prevalent mental illness and it affects the way people think, feel, talk and conduct their daily activities. The associated stigma often leads to misdiagnosis, posing risks such as disability and suicide. The study employed random forest algorithm to model the prevalence of depression among Murang’a University of technology (MUT) students. A sample of 1448 students from the different schools at the university participated in the study by completing questionnaires on sociodemographic and other factors associated with depression. The questionnaires were administered through social media platforms. Participants were selected using proportionate stratified random sampling and simple random sampling to ensure that a representative sample was chosen from each school. The data gathered was examined using descriptive and inferential statistics. Depression was measured using the Patient Health Questionnaire scale (PHQ-9). Using a cut-off point of 10, 25.97% students had depressive symptoms. This comprised of 19.61% moderate symptoms and 6.35% severe symptoms. The confusion matrix criteria were used to assess the performance of random forest in modeling depression prevalence among MUT students. Metrics for random forest included, accuracy (0.9868), sensitivity (0.95), specificity (1.00), positive predictive value (1.00), and negative predictive value (0.9824). Implementing targeted interventions founded on identified risk and protective factors and exploring the long-term outcomes of these interventions would contribute to the evolving field of mental health research within academic settings.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"27 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140413921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-29DOI: 10.9734/ajpas/2024/v26i3597
Kingdom Nwuju, I. B. Lekara-Bayo, S. N. Nwanneako, Y. A. Da-Wariboko
Aims: This study aims to analyze the complex relationship between the financial sector and economic growth in Nigeria. The study aims to provide comprehensive insights into this nexus by employing a comparative investigation using three distinct models: Linear Regression, Poisson Pseudo Maximum Likelihood (PPML), and Bayesian Vector Autoregression (BVAR). Methodology: The study then applied three different models, with a specific focus on the BVAR(2) model, supported by various diagnostic tests and stability assessments. The inclusion of Linear regression analysis and Poisson Pseudo Maximum Likelihood Estimator (PPML) enhances the depth of the study, providing nuanced insights into the impact of specific financial sector variables on economic growth. Results: The BVAR (2) model emerges as the optimal choice, demonstrating its reliability in capturing dynamic interactions and offering a powerful tool for policymakers. Specific results, such as the significant negative impact of D(CPS) in the regression analysis and the high R-squared in PPML, provide actionable insights into areas requiring policy interventions and underscore the substantial contribution of the financial sector to economic growth. Conclusion: The comparative assessment of model performances, favoring the BVAR model, guides future research and policy considerations, providing a reliable framework for further investigations. The study's insights are positioned as valuable for policymakers seeking to enhance economic growth through strategic interventions in the financial sector. Overall, the abstract succinctly encapsulates the aims, methodology, results, and concluding implications of the study on the nexus between the financial sector and economic growth in Nigeria.
目的：本研究旨在分析尼日利亚金融部门与经济增长之间的复杂关系。本研究旨在通过使用三种不同的模型进行比较调查，从而对这种关系提供全面的见解：线性回归、泊松伪最大似然（PPML）和贝叶斯向量自回归（BVAR）。研究方法：研究采用了三种不同的模型，重点是 BVAR(2) 模型，并辅以各种诊断测试和稳定性评估。线性回归分析和泊松伪最大似然估计法（PPML）的加入增强了研究的深度，为特定金融部门变量对经济增长的影响提供了细致入微的见解。研究结果BVAR（2）模型是最佳选择，证明了其在捕捉动态互动方面的可靠性，并为决策者提供了一个强有力的工具。具体结果，如回归分析中 D（CPS）的显著负面影响和 PPML 的高 R 平方，为需要政策干预的领域提供了可操作的见解，并强调了金融部门对经济增长的巨大贡献。结论对模型性能的比较评估倾向于 BVAR 模型，为未来的研究和政策考虑提供了指导，为进一步的调查提供了可靠的框架。该研究的见解对于寻求通过对金融部门的战略干预来促进经济增长的政策制定者来说非常有价值。总之，摘要简明扼要地概括了尼日利亚金融部门与经济增长之间关系研究的目的、方法、结果和结论意义。
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