Pub Date : 2024-02-23DOI: 10.9734/ajpas/2024/v26i2594
Oliver Mukweyi Pyoko
Organization expenses result from a company’s utilization of long-term debt in its capital structure. One can also characterize a firm’s size by looking at its assets. In order for a company to draw in investors, its worth increases with its size. The profitability of a business may be enhanced by including long-term obligations in its structure of capital since the interest paid on such debts is deduction for taxes. Therefore, this study aimed at examining the effect of firm size and profitability on long term debt of listed firms at the Nairobi Securities Exchange. The study was based on trade off theory and pecking order theory. Secondary data was obtained from the firms from 2007-2011. Panel data was used to analyze data observations. The result indicates that firm size had insignificant effect on long term debt of firms. Profitability had significant effect long term debt. The study recommends that larger firms should leverage their greater access to capital markets to secure long term debts financing at favorable terms, balancing the benefits of debt against potential risks. Firms also with high profitability should encourage internal financing sources to reduce reliance on external debt and minimize financial cost.
{"title":"Effect of Firm Size and Profitability on Long Term Debt of Firms Listed at the Nairobi Securities Exchange, Kenya","authors":"Oliver Mukweyi Pyoko","doi":"10.9734/ajpas/2024/v26i2594","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i2594","url":null,"abstract":"Organization expenses result from a company’s utilization of long-term debt in its capital structure. One can also characterize a firm’s size by looking at its assets. In order for a company to draw in investors, its worth increases with its size. The profitability of a business may be enhanced by including long-term obligations in its structure of capital since the interest paid on such debts is deduction for taxes. Therefore, this study aimed at examining the effect of firm size and profitability on long term debt of listed firms at the Nairobi Securities Exchange. The study was based on trade off theory and pecking order theory. Secondary data was obtained from the firms from 2007-2011. Panel data was used to analyze data observations. The result indicates that firm size had insignificant effect on long term debt of firms. Profitability had significant effect long term debt. The study recommends that larger firms should leverage their greater access to capital markets to secure long term debts financing at favorable terms, balancing the benefits of debt against potential risks. Firms also with high profitability should encourage internal financing sources to reduce reliance on external debt and minimize financial cost.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"17 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140436085","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 : 2024-02-20DOI: 10.9734/ajpas/2024/v26i2593
U. Sunday, Akpan, Ubong Dominic, Uwakwe Joy Ijeoma, Thomas, Henry Sylvester
This work, presents a formulation of mathematical model of bird harvesting in an intensive poultry system, under the assumption that under a favourable environmental atmosphere and good management system, the birds have logistic growth. The model is analysed using methods from dynamical system theory and theory of calculus. It was established that the system has two steady state, the two equilibrium state are both locally asymptotically stable. The first one is stable if there is a bound on the harvest rate of the birds, which is proportional to the growth rate of the birds. The second equilibrium state is locally asymptotically stable (LAS) if k < (frac{r(C+y)}{p}) that is if the carrying capacity is less than the ratio of the sum of and Per unit tax on the bird to that of Per unit price of the birds. Further analysis indicates that the limiting population of bird, that is the maximum population of birds that the available resources in the system can sustain and also ensures harvesting profitability is given as
这项研究提出了集约化家禽饲养系统中家禽收获的数学模型，假设在有利的环境氛围和良好的管理系统下，家禽的生长具有逻辑性。该模型采用动力系统理论和微积分理论的方法进行分析。结果表明，该系统有两个稳定状态，这两个平衡状态都是局部渐近稳定的。如果鸟类的收获率与鸟类的增长率成正比，则第一个平衡态是稳定的。如果 k < (frac{r(C+y)}{p})，即如果承载能力小于鸟类单位税额与鸟类单位价格之和的比值，则第二个均衡状态是局部渐近稳定的（LAS）。进一步分析表明，鸟类的极限种群数量，即系统中可用资源所能维持的最大鸟类种群数量，同时也能确保收获利润，其值为
{"title":"Mathematical Modeling of Bird Harvesting in Intensive Poultry System","authors":"U. Sunday, Akpan, Ubong Dominic, Uwakwe Joy Ijeoma, Thomas, Henry Sylvester","doi":"10.9734/ajpas/2024/v26i2593","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i2593","url":null,"abstract":"This work, presents a formulation of mathematical model of bird harvesting in an intensive poultry system, under the assumption that under a favourable environmental atmosphere and good management system, the birds have logistic growth. The model is analysed using methods from dynamical system theory and theory of calculus. It was established that the system has two steady state, the two equilibrium state are both locally asymptotically stable. The first one is stable if there is a bound on the harvest rate of the birds, which is proportional to the growth rate of the birds. The second equilibrium state is locally asymptotically stable (LAS) if k < (frac{r(C+y)}{p}) that is if the carrying capacity is less than the ratio of the sum of and Per unit tax on the bird to that of Per unit price of the birds. Further analysis indicates that the limiting population of bird, that is the maximum population of birds that the available resources in the system can sustain and also ensures harvesting profitability is given as ","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"130 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140448449","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 : 2024-01-31DOI: 10.9734/ajpas/2024/v26i1583
Ma’rufah Hayati, R. Permatasari
Rainfall plays a pivotal role in influencing agricultural production in Lampung province. The precision of rainfall predictions holds significant importance for enhancing agricultural yields in the region. One effective approach for modeling rainfall is Statistical Downscaling (SD), which employs statistical models to examine the correlation between large-scale (global) climatological data and small-scale (local) data. SD addresses the limitation of global scale data, such as the General Circulation Model (GCM), which lacks the resolution to directly forecast localized climate conditions like rainfall. Rainfall can be broadly categorized into continuous and discrete components. The continuous component delineates the intensity of rainfall, while the discrete component describes the occurrence of rain. Both components are integral to accurate rainfall predictions. The mixed Tweedie distribution, combining Gamma and Poisson distributions, is proficient in handling both continuous and discrete components of rainfall. GCMs commonly encounter multicollinearity issues in SD modeling, which can be mitigated through Principal Component Analysis. This study seeks to compare two regression models: the generalized linear model with a gamma response and the Tweedie compound response. Rainfall data from three distinct regions in Lampung province, representing high, medium, and lowlands, is utilized. The research findings indicate that, for high and lowlands, the Tweedie compound exhibits a smaller Root Mean Square Error of Prediction (RMSEP) compared to gamma. Conversely, in medium lands, gamma-GLM demonstrates a smaller RMSEP value than the Tweedie compound. Thus, the distribution of the Tweedie compound is better suited for use than Gamma-GLM, especially for high and lowland areas.
{"title":"Comparison of Generalized Linear Model between Gamma and Tweedie Compound Response for Rainfall Prediction in Lampung Province","authors":"Ma’rufah Hayati, R. Permatasari","doi":"10.9734/ajpas/2024/v26i1583","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i1583","url":null,"abstract":"Rainfall plays a pivotal role in influencing agricultural production in Lampung province. The precision of rainfall predictions holds significant importance for enhancing agricultural yields in the region. One effective approach for modeling rainfall is Statistical Downscaling (SD), which employs statistical models to examine the correlation between large-scale (global) climatological data and small-scale (local) data. SD addresses the limitation of global scale data, such as the General Circulation Model (GCM), which lacks the resolution to directly forecast localized climate conditions like rainfall. Rainfall can be broadly categorized into continuous and discrete components. The continuous component delineates the intensity of rainfall, while the discrete component describes the occurrence of rain. Both components are integral to accurate rainfall predictions. The mixed Tweedie distribution, combining Gamma and Poisson distributions, is proficient in handling both continuous and discrete components of rainfall. GCMs commonly encounter multicollinearity issues in SD modeling, which can be mitigated through Principal Component Analysis. This study seeks to compare two regression models: the generalized linear model with a gamma response and the Tweedie compound response. Rainfall data from three distinct regions in Lampung province, representing high, medium, and lowlands, is utilized. The research findings indicate that, for high and lowlands, the Tweedie compound exhibits a smaller Root Mean Square Error of Prediction (RMSEP) compared to gamma. Conversely, in medium lands, gamma-GLM demonstrates a smaller RMSEP value than the Tweedie compound. Thus, the distribution of the Tweedie compound is better suited for use than Gamma-GLM, especially for high and lowland areas.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"192 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140470787","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 : 2024-01-29DOI: 10.9734/ajpas/2024/v26i1578
Kexuan Li, Susie Sinks, Peng Sun, Lingli Yang
A bioequivalence study is a type of clinical trial designed to compare the biological equivalence of two different formulations of a drug. Such studies are typically conducted in controlled clinical settings with human subjects, who are randomly assigned to receive two formulations. The two formulations are then compared with respect to their pharmacokinetic profiles, which encompass the absorption, distribution, metabolism, and elimination of the drug. Under the guidance from Food and Drug Administration (FDA), for a size-(alpha) bioequivalence test, the standard approach is to construct a 100(1 - 2(alpha))% confidence interval and verify if the confidence interval falls with the critical region. In this work, we clarify that 100(1-2(alpha))% confidence interval approach for bioequivalence testing yields a size-(alpha) test only when the two one-sided tests in TOST are "equal-tailed". Furthermore, a 100(1 - (alpha))% confidence interval approach is also discussed in the bioequivalence study.
{"title":"Choosing Confidence Intervals in Bioequivalence Studies: 100(1 - 2(alpha) )% and 100(1 - (alpha) )% Approaches","authors":"Kexuan Li, Susie Sinks, Peng Sun, Lingli Yang","doi":"10.9734/ajpas/2024/v26i1578","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i1578","url":null,"abstract":"A bioequivalence study is a type of clinical trial designed to compare the biological equivalence of two different formulations of a drug. Such studies are typically conducted in controlled clinical settings with human subjects, who are randomly assigned to receive two formulations. The two formulations are then compared with respect to their pharmacokinetic profiles, which encompass the absorption, distribution, metabolism, and elimination of the drug. Under the guidance from Food and Drug Administration (FDA), for a size-(alpha) bioequivalence test, the standard approach is to construct a 100(1 - 2(alpha))% confidence interval and verify if the confidence interval falls with the critical region. In this work, we clarify that 100(1-2(alpha))% confidence interval approach for bioequivalence testing yields a size-(alpha) test only when the two one-sided tests in TOST are \"equal-tailed\". Furthermore, a 100(1 - (alpha))% confidence interval approach is also discussed in the bioequivalence study.","PeriodicalId":502163,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"46 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140488060","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}
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