Power modified XLindley distribution: Statistical properties and applications.

This research introduces a novel two-parameter distribution, the power-modified XLindley distribution, developed through the application of power transformation techniques to the existing modified XLindley distribution. This new distribution enhances flexibility and adaptability in statistical modeling. We conduct a thorough examination of its statistical properties, exploring its potential to improve data fitting and modeling accuracy. To assess the effectiveness of the model, we employ multiple estimation techniques and evaluate their performance through extensive simulation experiments. Our findings indicate that the maximum product of the spacings method is particularly effective for parameter estimation. To demonstrate the practical utility of the proposed model, we apply it to two real-world datasets: one related to flood data and the other to reliability engineering. The results underscore the distribution's superior ability to capture the characteristics of these datasets compared to existing models, highlighting its significance for applications in natural disaster analysis and reliability studies.

Sine π -power odd-G family of distributions with applications.

This paper investigates a novel category of probability distributions and a specific member within this category. We have formulated a new family of trigonometric distributions by utilizing the odds ratio derived from the distribution function of a base distribution. This newly devised distribution family termed the "Sine pie-power odd-G family" of distributions, is constructed through a transformation involving the sine function. The paper presents an overview of the fundamental characteristics inherent to this proposed distribution family. Using the Weibull distribution as a base reference, we have introduced a member belonging to the proposed distribution family. This member demonstrates various hazard functions such as j, reverse-j, increasing, decreasing, or bathtub shapes. The paper examines essential statistical attributes of this newly introduced distribution. The estimation of the distribution's parameters is carried out via the maximum likelihood estimation method. The accuracy of the parameter estimation procedure is validated through Monte Carlo simulations. The outcomes of these simulations reveal a reduction in biases and mean square errors as sample sizes increase, even for small samples. Two sets of real-engineering data are considered to demonstrate the proposed distribution's applicability. The performance of the suggested distribution is evaluated using some model selection criteria and goodness-of-fit test statistics. Empirical evidence from these evaluations substantiates that the proposed model outperforms six existing models.

Efficient imputation methods in case of measurement errors.

This manuscript develops few efficient difference and ratio kinds of imputations to handle the situation of missing observations given that these observations are polluted by the measurement errors (ME). The mean square errors of the developed imputations are studied to the primary degree approximation by adopting Taylor series expansion. The proposed imputations are equated with the latest existing imputations presented in the literature. The execution of the proposed imputations is assessed by utilizing a broad empirical study utilizing some real and hypothetically created populations. Appropriate remarks are made for sampling respondents regarding practical applications.

A new modified biased estimator for Zero inflated Poisson regression model.

Zero-inflated Poisson (ZIP) model is widely used for counting data with excessive zeroes. The multicollinearity is the common factor in the explanatory variables of the count data. In this context, typically, maximum likelihood estimation (MLE) generates unsatisfactory results due to inflation of mean square error (MSE). In the solution of this problem usually, ridge parameters are used. In this study, we proposed a new modified zero-inflated Poisson ridge regression model to reduce the problem of multicollinearity. We experimented within the context of a specified simulation strategy and recorded the behavior of proposed estimators. We also apply our proposed estimator to the real-life data set and explore how our proposed estimators perform well in the presence of multicollinearity with the help of ZIP model for count data.

A novel extension of half-logistic distribution with statistical inference, estimation and applications.

In the present study, we develop and investigate the odd Frechet Half-Logistic (OFHL) distribution that was developed by incorporating the half-logistic and odd Frechet-G family. The OFHL model has very adaptable probability functions: decreasing, increasing, bathtub and inverted U shapes are shown for the hazard rate functions, illustrating the model's capacity for flexibility. A comprehensive account of the mathematical and statistical properties of the proposed model is presented. In estimation viewpoint, six distinct estimation methodologies are used to estimate the unknown parameters of the OFHL model. Furthermore, an extensive Monte Carlo simulation analysis is used to evaluate the effectiveness of these estimators. Finally, two applications to real data are used to demonstrate the versatility of the suggested method, and the comparison is made with the half-logistic and some of its well-known extensions. The actual implementation shows that the suggested model performs better than competing models.

Adolescents' perceptions of active school transport in northern Sweden.

Active school transport (AST) refers to using active means of transport such as walking, cycling, or riding a non-motorised scooter to school. It can help improve adolescents' physical activity levels and create a more sustainable environment. The study involved 70 adolescents (45 boys and 25 girls) aged 13 to 14 from one school in Skellefteå, in Northern Sweden. In an online questionnaire, they were asked about their perceptions of cycling, walking, and riding a non-motorised scooter to school. This study used descriptive statistics, multiple regression analysis, and hypothesis testing with ANOVA to analyse the collected data and compare the perceptions of different types of transport on safety, environmental, and personal factors among adolescents in Northern Sweden. According to the results, more adolescents walked to school than cycled, and significantly few rode a non-motorised scooter to school. Most adolescents believe walking or cycling to school is a great way to exercise. Furthermore, the study also revealed that many adolescents avoid using AST due to the time it takes. Although the study showed that adolescents felt sufficient support for using AST from schools and parents, the number of adolescents using motorised transport is higher during winter than in summer. Additionally, most of them were more confident about cycling and walking to school than riding a non-motorised scooter and thought using AST was nice. Finally, most adolescents perceived having complete control over their transport options when going to school. The research indicates that it is crucial to implement interventions that inspire children to be interested and excited about using AST. These strategies should include fostering an AST culture that is fun and positive, as well as creating environments that are safe and supportive. The research results will guide the creation of a persuasive game that can motivate adolescents to use AST and measure its effectiveness.

Bibliometric structured review of tuberculosis in Nigeria.

Background: The tuberculosis burden is growing in Nigeria along with its population. For example, Nigeria has the sixth highest TB burden globally, with an estimated 4.3 per cent multi-drug resistance in new cases. This study builds on the existing study that examined academic involvement in tuberculosis research. The study in question focused on global medical literature related to tuberculosis, but the non-visibility of some low and middle-income countries in the bigger global picture motivated this present study. Every year, over 245,000 Nigerians succumb to tuberculosis (TB), with approximately 590,000 new cases reported (of these, around 140,000 are also HIV-positive). This study carried out an academic publication evaluation with the VOS viewer tool to map bibliometric data for scholarly articles published between 1991 and 2021 on tuberculosis research and used the Biblioshiny app for analytics and plots of authors, sources, and documents to explore the descriptive statistics of tuberculosis literature. The present study delineates that England has the highest collaborating country with Nigeria in the study of tuberculosis over the years and according to the report, the University of Nigeria, the University of Ibadan, and Nnamdi Azikwe University are Nigerian institutions with extensive collaborations. This study concludes with managerial implications for future actions.

Prevalence and Potential Determinants of Aggregate Anthropometric Failure among Pakistani Children: Findings from a Community Health Survey.

Malnutrition among children is an important public health problem in Pakistan. Conventional indicators (stunting, wasting and underweight) are well known. However, there is a need for aggregate indicators in this perspective. The goal of this study is to assess the prevalence and trends of malnutrition among Pakistani children under the age of five using the so-called composite index of anthropometric failure (CIAF), a tool for calculating the whole aggregate burden of malnutrition. The data were extracted from the Pakistan Demographic and Health Survey 2012-2013. Mothers' education and socioeconomic statuses (SES) were assessed as important factors in malnutrition. Chi-squared analysis was used to check the bivariate association, and multiple logistic regression was used to identify the significant correlates of child malnutrition. Moreover, multiple correspondence analysis (MCA) was applied to strengthen the use of CIAF as an outcome variable. The study looked at 3071 children under the age of five, with 52.2% of them falling into the CIAF. Children of educated mothers had 43% fewer odds of being malnourished (OR (Odd Ratio) = 0.57, 95% CI (Confidence Interval) = 0.44-0.73). Additionally, a decreasing trend in malnutrition was found with increasing SES. There is a need to improve maternal education. Such programs focusing on increasing women's autonomy in making home decisions should be established. Furthermore, long-term interventions for improving home SES and effective nutritional methods should be examined. For policymakers, the use of CIAF is suggested since it provides an estimate of the entire burden of undernutrition.

The modified beta transmuted family of distributions with applications using the exponential distribution.

In this work, a new family of distributions, which extends the Beta transmuted family, was obtained, called the Modified Beta Transmuted Family of distribution. This derived family has the Beta Family of Distribution and the Transmuted family of distribution as subfamilies. The Modified beta transmuted frechet, modified beta transmuted exponential, modified beta transmuted gompertz and modified beta transmuted lindley were obtained as special cases. The analytical expressions were studied for some statistical properties of the derived family of distribution which includes the moments, moments generating function and order statistics. The estimates of the parameters of the family were obtained using the maximum likelihood estimation method. Using the exponential distribution as a baseline for the family distribution, the resulting distribution (modified beta transmuted exponential distribution) was studied and its properties. The modified beta transmuted exponential distribution was applied to a real life time data to assess its flexibility in which the results shows a better fit when compared to some competitive models.

Generalized cure rate model for infectious diseases with possible co-infections.

This research mainly aims to develop a generalized cure rate model, estimate the proportion of cured patients and their survival rate, and identify the risk factors associated with infectious diseases. The generalized cure rate model is based on bounded cumulative hazard function, which is a non-mixture model, and is developed using a two-parameter Weibull distribution as the baseline distribution, to estimate the cure rate using maximum likelihood method and real data with R and STATA software. The results showed that the cure rate of tuberculosis (TB) patients was 26.3%, which was higher than that of TB patients coinfected with human immunodeficiency virus (HIV; 23.1%). The non-parametric median survival time of TB patients was 51 months, while that of TB patients co-infected with HIV was 33 months. Moreover, no risk factors were associated with TB patients co-infected with HIV, while age was a significant risk factor for TB patients among the suspected risk factors considered. Furthermore, the bounded cumulative hazard function was extended to accommodate infectious diseases with co-infections by deriving an appropriate probability density function, determining the distribution, and using real data. Governments and related health authorities are also encouraged to take appropriate actions to combat infectious diseases with possible co-infections.