Discriminant Analysis and It’s Application to the Oil Palm Cultivation in Nigeria

Rasheed Saheed Lekan

Asian Journal of Probability and Statistics, Page 315-323
DOI: 10.9734/ajpas/2021/v15i430382

There are various environmental factors that need to be considered when assessing the suitability of site for oil palm cultivation some of which are; climate, vegetation, and the soils. Using soil morphology and degree of profile development or the nature of the parent bedrock and the vegetation formed grouped the soil supporting oil palm as generally belonging to five parent materials. The various soil groups includes:- Crystalline metamorphic and Igneous rocks, Shale mixed with sand stone and clay, Coastal plain sand, Coastal alluvium and Fresh water swamp, these groups are presumed to differ on several physiochemical properties and formed the basis on which land is being selected for oil palm cultivation. The classification of soil location in future into any of the five soil types on the basis of the soil characteristics can be facilitated using different approach, but in this study, discriminant analysis will be used to measure the success rate of classifying the soil types by using the physiochemical properties soils in the Raphia growing zone of Nigeria. The research is aimed at applying discriminant analysis thereby satisfying the following objectives: Use discriminant analysis to predict soil group membership in order to correctly classify future unknown observation into any of the five soil groups based on the observed predictors (soil characteristics) in soils supporting Raphia palms of southern Nigeria, Form linear combinations of the discriminating predictor variables that differs significantly in their group means, Identify the soil properties that best discriminates among the soil types. The findings revealed the utility of several multivariate statistical methods for soil research, as well as a better knowledge of soil heterogeneity in Nigeria's oil palm area. This information will be important in measuring soil diversity for crop enhancement and in developing agricultural management strategies, particularly in Nigeria's oil palm area.

Note on Quasi Lindley Distribution: Some Remarks and Corrections

Chaabane Benatmane, Halim Zeghdoudi, Abdelali Ezzebsa, Lahsen Bouchahed

Asian Journal of Probability and Statistics, Page 324-329
DOI: 10.9734/ajpas/2021/v15i430383

Some remarks and corrections of some properties the new distribution, quasi Lindley, of which the Lindley distribution is a special case, are given concerning its parameter space. In addition, a comparison study between the new two-parameter distributions (pseudo Lindley, gamma Lindley, quasi Lindley and two-parameter Lindley) is studied.

Examining the Factors Affecting the Success of the Establishment of Village-Owned Enterprises

. Solimun, Indah Yanti, Adi Kusumaningrumi, Agus Wahyu Widodo

Asian Journal of Probability and Statistics, Page 1-9
DOI: 10.9734/ajpas/2021/v15i430358

Aims: This study aims to analyze the influence of Village Government Policies, Village Financial Institutions, Resources, and Community Factors on the Success of the Establishment of Village-Owned Enterprises (VOE) with Village Government Support as moderating variables.

Study Design: SEM WarpPLS.

Place: Sumberputih Village, East Java, Indonesia.

Methodology: This research is quantitative research. The research instrument used a questionnaire. The research was conducted in Sumberputih Village, East Java, Indonesia. The sampling process used a simple random sampling technique and obtained 100 respondents. Data analysis using SEM WarpPLS.

Results: The results showed that the Village Government Policy, Village Financial Institutions, Resources, and Community Factors had a significant effect on the success of the establishment of VOE (Y). Meanwhile, Village Government Support cannot moderate the influence of the four variables on the success of VOE establishment.

Split Domination In Interval-valued Fuzzy Graphs

Nojood A. AL-Khadari, Mahiuob M. Q. Shubatah

Asian Journal of Probability and Statistics, Page 10-20
DOI: 10.9734/ajpas/2021/v15i430360

Aims / Objectives: In this paper, we introduced and investigated the concept of split domination in interval-valued fuzzy graph and denoted by γs. We obtained many results related to γs. We investigated and study the relationship of γs with other known parameters in interval-valued fuzzy graph. Finally we calculated γs(G) for some standard interval valued fuzzy graphs.

Bayesian Regression of Government Expenditure on Revenue in Nigeria

Olawale Basheer Akanbi

Asian Journal of Probability and Statistics, Page 21-37
DOI: 10.9734/ajpas/2021/v15i430361

The relationship between government expenditure and its revenue is generating serious debate among researchers. Similarly, their has been a controversy between the classical and the bayesian modelling. Therfore, this study examined the relationship between the government expenditure and its revenue in Nigeria using the bayesian approach. The finance data extracted from the Central Bank of Nigeria statistical bulletin from 1989 to 2018 were considered for the study. Bayesian linear regression was used to fit the model. Normal distribution was fit for the likelihood. Thus, normal-gamma prior was elicited for the bayesian regression parameters. The result showed that the Bayesian estimates with elicited normal-gamma prior produced a better posterior mean of 0.536 for the Total Revenue with a smaller posterior standard deviation of 0.00001 when compared with the OLS standard deviation of 0.05256. Similarly, the total revenue explained 78% variations in the Total expenditure. The constructed model fit was: Total Expenditure = 98.57128 + 0.53630* Total Revenue. This showed that a naira unit of the total expenditure will always be increased by 0.54 of the total revenue. Forecast of 30 years for the total expenditure using both OLS and Bayesian (normal gamma prior) were increasing as the years were progressing. Government should look for a way to increase its revenue in order to sustain the future expenses of the government since expenditure increases yearly.

Probabilistic Method for Estimating the Level of Reliability of Solar Photovoltaic Systems for Households in Ghana

Ali Abubakar, Anas Musah, Frank Kofi Owusu, Isaac Afari Addo

Asian Journal of Probability and Statistics, Page 38-53
DOI: 10.9734/ajpas/2021/v15i430362

Renewable Energy Resources have been identified among the most promising sources of harnessing power for industrial and household consumption but their power generations highly uctuate so building renewable power systems without critical reliability analysis might result in frequent blackouts in the power system. Therefore, in this paper, a robust, effective and ecient design approach is proposed to handle the reliability issues. The study involves a Mathematical modelling strategy of the PV system to estimate the total PV power produced and the Bottom-Up approach for predicting the household load demand. The reliability is defined in terms of Loss of Load Probability. The design methodology was validated with a University Household. The data used for the analysis consists of daily average global solar irradiance and load profiles. The results revealed that throughout the year, November-February is where the system seems to be more reliable. Also, the results indicated that without buck-up systems, the system would experience an average annual power loss of 17.8753% and thus, it is recommended that either solar batteries or the grid are used as backup system to achieve a complete level of reliability.

The Second Hyper-Zagreb Index of Complement Graphs and Its Applications of Some Nano Structures

Mohammed Alsharafi, Yusuf Zeren, Abdu Alameri

Asian Journal of Probability and Statistics, Page 54-75
DOI: 10.9734/ajpas/2021/v15i430364

In chemical graph theory, a topological descriptor is a numerical quantity that is based on the chemical structure of underlying chemical compound. Topological indices play an important role in chemical graph theory especially in the quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR). In this paper, we present explicit formulae for some basic mathematical operations for the second hyper-Zagreb index of complement graph containing the join G1 + G2, tensor product G1 $$\otimes$$ G2, Cartesian product G1 x G2, composition G1 $$\circ$$ G2, strong product G1 * G2, disjunction G1 V G2 and symmetric difference G1 $$\oplus$$ G2. Moreover, we studied the second hyper-Zagreb index for some certain important physicochemical structures such as molecular complement graphs of V-Phenylenic Nanotube V PHX[q, p], V-Phenylenic Nanotorus V PHY [m, n] and Titania Nanotubes TiO2.

An Application of the Growth Model to HIV/AIDS Patients on Antiretroviral Therapy with Coinfections in a District Hospital in Ghana

Michael Fosu Ofori, Aliyu Mohammed, Kofi Mensah

Asian Journal of Probability and Statistics, Page 76-87
DOI: 10.9734/ajpas/2021/v15i430365

Lethal opportunistic diseases like Tuberculosis and Hepatitis C are deeply ingrained complications for patients diagnosed with human immunodeficiency virus (HIV).  The effect of Highly Active Antiretroviral Therapy (HAART) on Hepatitis C and Tuberculosis in HIV patients in Ghana continues to be unpredictable, especially in younger patients. This study aimed to describe the patient survival time distribution on antiretroviral treatment using Statistical Growth model. A retrospective cohort of 634 patients aged between 22 to 73 years were selected from the District Health Information Management System 2 (DHIMS 2), a secondary source, using a random sampling approach. These patients were diagnosed with HIV and started antiretroviral therapy between 2000 and 2019 at St. Martins Catholic Hospital in Amansie South District of the Ashanti Region. The probability of survival for almost all of the risk factors decreases gradually at different clinical states, i.e., from state 1 through to state 4. Hepatitis C or Tuberculosis can also be diagnosed chronically in approximately one in ten patients. Age, sex and the CD4 cell count of patients substantially (p- value =0.001 in log-rank tests) contributed to the prevalence of human immunodeficiency virus. Survival of infants, aged <1year, after treatment was of negative effect. The statistical growth analytical approach offers a good estimate of survival rate ( 79.82%) among major risk factors for infants, aged <1yearon ART with proportion of survival growth of 0.95, hence the survival time of infants, aged <1yearon HAART is negatively affected irrespective of the treatment initiation period.

Statistical Distribution of Lassa Fever in Edo State, Nigeria

Nwaigwe, Chrysogonus Chinagorom, Bartholomew, Desmond Chekwube, Eze, Petra Adachukwu

Asian Journal of Probability and Statistics, Page 88-96
DOI: 10.9734/ajpas/2021/v15i430366

Lassa fever is a severe viral infection caused by the Lassa virus and spread by contact with excretions or secretions of infected rats gaining access to food and water inside human houses and other human activity areas. Sierra Leone, the Republic of Guinea, Nigeria, and Liberia are among the nations where it is endemic with a high number of deaths recorded yearly due to Lassa fever. In Nigeria, one of the states with the highest incidence is Edo. In order to reduce and predict the spread of Lassa fever in Edo state, the trend of the disease needs to be understood. Knowledge of the statistical distribution of a disease is one of the best ways to understand the trend of the disease. Currently, existing research on the statistical distribution of Lassa fever is very rare. The present work is an attempt to initiate research on the statistical distribution of Lassa fever with data obtained on weekly cases of Lassa Fever in Edo State, Nigeria. Based on the Kolmogorov Smirnoff and Anderson Darling’s goodness of fit test for fitting distribution, the Geometric distribution outfitted the weekly confirmed incidences of Lassa fever in Edo State, Nigeria when compared with the Discrete Uniform and Poisson distributions. The study further revealed that on the average, two Lassa fever cases is recorded per week in Edo State within the study period. This number of cases per week is on the high side and should be immediately looked into.

Gerber-Shiu Function in a Discrete-time Risk Model with Dividend Strategy

Junqing Huang, Zhenhua Bao

Asian Journal of Probability and Statistics, Page 97-110
DOI: 10.9734/ajpas/2021/v15i430367

In this paper, a discrete-time risk model with dividend strategy and a general premium rate is considered. Under such a strategy, once the insurer’s surplus hits a constant dividend barrier , dividends are paid off to shareholders at  instantly. Using the roots of a generalization of Lundberg’s fundamental equation and the general theory on difference equations, two difference equations for the Gerber-Shiu discounted penalty function are derived and solved. The analytic results obtained are utilized to derive the probability of ultimate ruin when the claim sizes is a mixture of two geometric distributions. Numerical examples are also given to illustrate the applicability of the results obtained.

Kumaraswamy-Janardan Distribution: A Generalized Janardan Distribution with Application to Real Data

Nelson Doe Dzivor, Henry Otoo, Eric Neebo Wiah

Asian Journal of Probability and Statistics, Page 111-122
DOI: 10.9734/ajpas/2021/v15i430368

The quest to improve on flexibility of probability distributions motivated this research. Four-parameter Janardan generalized distribution known as Kumaraswamy-Janardan distribution is proposed through method of parameterization and studied. The probability density function, cumulative density function, survival rate function as well as hazard rate function of the distribution are established. Statistical properties such as moments, moment generating function as well as maximum likelihood of the model are discussed. The parameters are estimated using the simulated annealing optimization algorithm.   Flexibility of the model in comparison with the baseline model as well as other competing sub-models is verified using Akaike Information Criteria (AIC). The model is tested with real data and is proven to be more flexible in fitting real data than any of its sub-models considered.

Queing Theory, a Tool for Polio Eradication in Nigeria

Raphael Ayan Adeleke, Ibrahim Ismaila Itopa, Sule Omeiza Bashiru

Asian Journal of Probability and Statistics, Page 123-133
DOI: 10.9734/ajpas/2021/v15i430369

To curb the spread of contagious diseases and the recent polio outbreak in Nigeria, health departments must set up and operate clinics to dispense medications or vaccines. Residents arrive according to an external (not necessarily Poisson) Arrival process to the clinic. When a resident arrives, he goes to the first workstation, based on his or her information, the resident moves from one workstation to another in the clinic. The queuing network is decomposed by estimating the performance of each workstation using a combination of exact and approximate models. A key contribution of this research is to introduce approximations for workstations with batch arrivals and multiple parallel servers, for workstations with batch service processes and multiple parallel servers, and for self service workstations. We validated the models for likely scenarios using data collected from one of the states vaccination clinics in the country during the vaccination exercises.

Modeling Coronavirus Pandemic Using Univariate and Multivariate Models: The Nigerian Perspective

Asian Journal of Probability and Statistics, Page 134-143
DOI: 10.9734/ajpas/2021/v15i430370

Corona virus Disease, a disease which was discovered in December, 2019 has been spreading worldwide like wildfire. In view of this, there is need of continuous findings on the impact, consequence and possible medications of the pandemic in Nigeria and the world at large. Therefore, this research is aimed at Analyzing the spread of Coronavirus pandemic in Nigeria, using univariate and multivariate models namely;(ARIMA) and (ARIMAX). The daily data used in this research was obtained from the NCDC official website dated from 19th April, 2020 to 20th April, 2021 with total of 384 observations using R and Eview10 software for the analysis. Three different variables were examined. The variables are; total confirmed, discharged and death cases for the purpose of establishing reliable forecast, for better decision making and a helping technique for drastic action in reducing the day to day spread of the pandemic. Summary statistics and stationary test were checked with the data being stationary at the first difference and design technique was conducted as well. Also, best fitted model was selected using Akaike Information Criteria (AIC). The ARIMA (1,1,3) model with an exogenous variable was chosen from the ARIMA models with minimum AIC. From the model, a prediction of sixty-days forecast showed the upward trend of the total confirmed cases of the pandemic in the country. The government on its part via its task force can use the predicted line to take much necessary measures and emphases on taking COVID-19 vaccines so as to prevent further spread of the virus

An Introspective Overview of the Dynamics of Recurrent Events Data Analysis

Anthony Joe Turkson, Timothy Simpson, John Awuah Addor

Asian Journal of Probability and Statistics, Page 144-162
DOI: 10.9734/ajpas/2021/v15i430371

A recurrent event remains the outcome variable of interest in many biometric studies. Recurrent events can be explained as events of defined interest that can occur to same person more than once during the study period. This study presents an overview of different pertinent recurrent models for analyzing recurrent events.

Aims: To introduce, compare, evaluate and discuss pros and cons of four models in analyzing recurrent events, so as to validate previous findings in respect of the superiority or appropriateness of these models.

Study Design:  A comparative studies based on simulation of recurrent event models applied to a tertiary data on cancer studies.

Methodology: Codes in R were implemented for simulating four recurrent event models, namely; The Andersen and Gill model; Prentice, Williams and Peterson models; Wei, Lin and Weissferd; and Cox frailty model. Finally, these models were applied to analyze the first forty subjects from a study of Bladder Cancer Tumors. The data set contained the first four repetitions of the tumor for each patient, and each recurrence time was recorded from the entry time of the patient into the study. An isolated risk interval is defined by each time to an event or censoring.

Results: The choice and usage of any of the models lead to different conclusions, but the choice depends on: risk intervals; baseline hazard; risk set; and correlation adjustment or simplistically, type of data and research question. The PWP-GT model could be used if the research question is focused on whether treatment was effective for the  event since the previous event happened. However, if the research question is designed to find out whether treatment was effective for the  event since the start of treatment, then we could use the PWP- TT. The AG model will be adequate if a common baseline hazard could be assumed, but the model lacks the details and versatility of the event-specific models. The WLW model is very suitable for data with diverse events for the same person, which underscores a potentially different baseline hazard for each type.

Conclusion: PWP-GT has proven to be the most useful model for analyzing recurrent event data.

Bivariate Compound Exponentiated Survival Function of the Lomax Distribution: Estimation and Prediction

R. M. Refaey, G. R. AL-Dayian, A. A. EL-Helbawy, A. A. EL-Helbawy

Asian Journal of Probability and Statistics, Page 163-184
DOI: 10.9734/ajpas/2021/v15i430372

In this paper, bivariate compound exponentiated survival function of the Lomax distribution is constructed based on the technique considered by AL-Hussaini (2011). Some properties of the distribution are derived. Maximum likelihood estimation and prediction of the future observations are considered. Also, Bayesian estimation and prediction are studied under squared error loss function. The performance of the proposed bivariate distribution is examined using a simulation study. Finally, a real data set is analyzed under the proposed distribution to illustrate its flexibility for real-life application.

Relationship among Continuous Probability Distributions and Interpolation

Kelachi P. Enwere, Uchenna P. Ogoke

Asian Journal of Probability and Statistics, Page 196-210
DOI: 10.9734/ajpas/2021/v15i430374

Aims: The Study seeks to determine the relationship that exists among Continuous Probability Distributions and the use of Interpolation Techniques to estimate unavailable but desired value of a given probability distribution.

Study Design: Statistical Probability tables for Normal, Student t, Chi-squared, F and Gamma distributions were used to compare interpolated values with statistical tabulated values. Charts and Tables were used to represent the relationships among the five probability distributions.

Methodology: Linear Interpolation Technique was employed to interpolate unavailable but desired values so as to obtain approximate values from the statistical tables. The data were analyzed for interpolation of unavailable but desired values at 95% a-level from the five continuous probability distribution.

Results: Interpolated values are as close as possible to the exact values and the difference between the exact value and the interpolated value is not pronounced. The table and chart established showed that relationships do exist among the Normal, Student-t, Chi-squared, F and Gamma distributions.

Conclusion: Interpolation techniques can be applied to obtain unavailable but desired information in a data set. Thus, uncertainty found in a data set can be discovered, then analyzed and interpreted to produce desired results. However, understanding of how these probability distributions are related to each other can inform how best these distributions can be used interchangeably by Statisticians and other Researchers who apply statistical methods employed in practical applications.

Exponentiated Frechet Distribution with Application in Temperature of Assam, India Overview with New Properties and Estimation

Umme Habibah Rahman, Tanusree Deb Roy

Asian Journal of Probability and Statistics, Page 211-225
DOI: 10.9734/ajpas/2021/v15i430375

In this paper, a new kind of distribution has suggested with the concept of exponentiate. The reliability analysis including survival function, hazard rate function, reverse hazard rate function and mills ratio has been studied here. Its quantile function and order statistics are also included. Parameters of the distribution are estimated by the method of Maximum Likelihood estimation method along with Fisher information matrix and confidence intervals have also been given. The application has been discussed with the 30 years temperature data of Silchar city, Assam, India. The goodness of fit of the proposed distribution has been compared with Frechet distribution and as a result, for all 12 months, the proposed distribution fits better than the Frechet distribution.

Impact of Measurement Error on the Power Function of Average Control Chart under Non-Normal Population

U. Mishra, J. R. Singh

Asian Journal of Probability and Statistics, Page 226-234
DOI: 10.9734/ajpas/2021/v15i430376

In the present article, effect of measurement error on the power function of control charts for mean with control limits is considered based on non-normal population. The non-normality is represented by the first four terms of an Edge-worth series. Tabular and visual comparison is also provided for the better comprehension of the significance of measurement error on power function under non-normality.

On The Efficiency of Almost Unbiased Mean Imputation When Population Mean of Auxiliary Variable is UnknownOn The Efficiency of Almost Unbiased Mean Imputation When Population Mean of Auxiliary Variable is Unknown

A. Audu, A. Danbaba, S. K. Ahmad, N. Musa, A. Shehu, A. M. Ndatsu, A. O. Joseph

Asian Journal of Probability and Statistics, Page 235-250
DOI: 10.9734/ajpas/2021/v15i430377

Human-assisted surveys, such as medical and social science surveys, are frequently plagued by non-response or missing observations. Several authors have devised different imputation algorithms to account for missing observations during analyses. Nonetheless, several of these imputation schemes' estimators are based on known population meanof auxiliary variable. In this paper, a new class of almost unbiased imputation method that uses  as an estimate of is suggested. Using the Taylor series expansion technique, the MSE of the class of estimators presented was derived up to first order approximation. Conditions were also specified for which the new estimators were more efficient than the other estimators studied in the study. The results of numerical examples through simulations revealed that the suggested class of estimators is more efficient.

Comparative Performance of ARIMA and GARCH Model in Forecasting Crude Oil Price Data

Atanu, Enebi Yahaya, Ette, Harrison Etuk, Amos, Emeka

Asian Journal of Probability and Statistics, Page 251-275
DOI: 10.9734/ajpas/2021/v15i430378

This study compares the performance of Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroskedasticity models in forecasting Crude Oil Price data as obtained from (CBN 2019) Statistical Bulletin.  The forecasting of Crude Oil Price, plays an important role in decision making for the Nigeria government and all other sectors of her economy. Crude Oil Prices are volatile time series data, as they have huge price swings in a shortage or an oversupply period. In this study, we use two time series models which are Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heterocedasticity (GARCH) models in modelling and forecasting Crude Oil Prices. The statistical analysis was performed by the use of time plot to display the trend of the data, Autocorrelation Function (ACF), Partial Autocorrelation Functions (PACF), Dickey-Fuller test for stationarity, forecasting was done based on the best fit models for both ARIMA and GARCH models. Our result shows that ARIMA (3, 1, 2) is the best ARIMA model to forecast monthly Crude Oil Price and we also found GARCH (1, 1) model is the best GARCH model and using a specified set of parameters, GARCH (1, 1) model is the best fit for our concerned data set.

An Alternative Hybrid Estimator of Finite Population Mean in Simple Random Sampling

T. Uba, A. J. Ikughur, S. C. Nwaosu

Asian Journal of Probability and Statistics, Page 276-298
DOI: 10.9734/ajpas/2021/v15i430379

In this paper, we propose an alternative hybrid estimator of finite population mean in simple random sampling without replacement (SRSWOR). This proposed estimator is a modification of Rashid et al. [1] estimator. The expressions for the bias and Mean Square Error (MSE) of the estimator are derived. A comprehensive simulation study to show the efficacy of the estimator as compared to conventional estimators using Coefficient of Variation as a performance measure. The results are also supported with empirical illustrations using real life data which have shown that the proposed estimator was more efficient than almost all the existing estimators considered in this study.

On the Revenue Generation of the Internally Generated Funds across Twifo Hemang Lower Denkyira District Assembly

Bridget Sena Borbor, Joshua Kwaku Hodinyah, Ali Abubakar

Asian Journal of Probability and Statistics, Page 299-306
DOI: 10.9734/ajpas/2021/v15i430380

Balancing the budget is one of the most important concerns of financial policy. Improving the quality of revenue and expenditure projections has become essential for policymakers. However, The most crucial component in sustaining success in terms of revenue generation and other grounds is time. Keeping up with the speed of time is difficult. A time series model is one such method for dealing with time-based data. The time series model is an adequate model when there are serially correlated data. Autoregressive Moving Averages (ARMA) is the appropriate approach when the error(s) of the data has the same variance regardless of the value taken by the independent variable(s).  For this reason, an internally generated fund data were collected from the Twifo Hemang Lower Denkyira District assembly from 2013 to 2019 which was subjected to descriptives and time series analysis. From the time series analysis, ARMA (1, 1) was selected as the best model using the AIC value and fit the observed monthly internally generated fund pattern. The study revealed among others that January 2020 will record the highest revenue generation of 21465.96 cedis over the two years forecast followed by March 2020, 19023.17 cedis  and May 2021 of 18122.05 cedis. The study also recommended among others that the authorities of Twifo Hemang Lower Denkyira District assembly should embark on educating the citizens on the need to pay their taxes for developmental progress of their assembly.

Fixed Point Results for Rational Type Contraction in A-Metric Spaces

Babita Pandey, Manoj Ughade, Amit Kumar Pandey

Asian Journal of Probability and Statistics, Page 307-314
DOI: 10.9734/ajpas/2021/v15i430381

The goal of this paper is to define rational contraction in the context of A-metric spaces and to develop various fixed-point theorems in order to elaborate, generalize, and synthesize several previously published results. Finally, to illustrate the new theorem, an example is given.

Unit Monsef Distribution with Regression Model

M. M. E. Abd El-Monsef, N. M. Sohsah, W. A. Hassanein

Asian Journal of Probability and Statistics, Page 330-340
DOI: 10.9734/ajpas/2021/v15i430384

The aim of this paper is introduced a new distribution with one parameter called unit Monsef distribution (UMD) with it is regression model since it is more fitting than well-known distributions in educational attainment data , derived from a transformation on Monsef distribution. it is probability function has been generated also distribution function. reliability function and hazard function, some of statistical measures are investigated such like moments of origin point, central moments, Lorenz and Bonferroni curves also stress strengths parameter are investigated. parameter estimated is obtained by using more than method like maximum likelihood method, method of moment and least square method. the simulation scheme for unit Monsef parameters. Finally, real data is used for studying the flexibility of UMD also applied on UMD regression model compared with others well Known distributions.

Weighted Log-Pearson Type Iii Distribution: Properties, Estimation and Application

Umme Habibah Rahman, Tanusree Deb Roy

Asian Journal of Probability and Statistics, Page 341-350
DOI: 10.9734/ajpas/2021/v15i430385

In this paper, we have proposed a new version of three parameters log-Pearson type III distribution known as weighted Log-Pearson type III distribution. The different structural properties of the newly model have been studied. The maximum likelihood estimators of the parameters and the Fishers information matrix have been discussed. Finally, a real-life data set has been analyzed.

Modelling by Simulations Monte Carlo of First Historical Zika Outbreak in Salta, Argentina, Occurred in 2017

Juan Carlos Rosales, Juan Pablo Aparicio, Pablo Quintana, Celeste Herrera, Betina Abad

Asian Journal of Probability and Statistics, Page 351-364
DOI: 10.9734/ajpas/2021/v15i430386

Scopes and Objectives: We analyzed some aspects of the first historical outbreak of Zika that occurred in Salta, Argentina, in the year 2017. We obtained elementary estimates, such as the prevalence ratio and describe the probabilistic behavior of the outbreak by simulation of type Monte Carlo.

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 December 2020 to September 2021.

Methodology: Descriptive and computational experiment analysis. Estimates of parameters and Simulation of type Monte Carlo.

Results: We describe the probabilistic behavior through Monte Carlo simulation of the first historical outbreak of Zika in Salta Argentina, 2017. Based on the data of registered Zika cases, we estimate a probabilistic model for it. We also spatially describe the outbreak by estimating the prevalence ratio. Finally, by computational experiment we generate epidemic outbreaks with 10, 20 and 30 runs, determining the intrinsic growth rate and estimating the basic reproductive number R0 for a generation time that takes into account both man and mosquito. We find that the estimates are significantly affected for the simulation type factor of 10 runs. The computational experiment shows that the descriptions of the outbreak and the estimates of R0 obtained, if the number of repetitions of the experiment corresponds to 20 and 30 runs, are qualitatively acceptable.

A New Trivariate Semicopula Using Rüschendorf Method

M. M. E. Abd EL-Monsef, M. M. Seyam, S. M. Elsobky

Asian Journal of Probability and Statistics, Page 365-371
DOI: 10.9734/ajpas/2021/v15i430388

In this paper we have introduced semicopula function by using Rüschendorf method, semicopula  which is related to correlation between one or more random variables and this way is more flexible than traditional correlation approaches and dependency among variables. Every semicopula has density associated with it, which is similar to the probability density of a multivariate distribution. Our purpose is developing a new trivariate semicopula under conditions which is a trivariate cumulative distribution with uniform marginal distribution on the interval [0,1].  In order to choose a random function under specific conditions, we rely on utilizing Rüschendorf method. As a result, we will discuss that in this paper. In this theme we select an arbitrary trivariate function which adopts the Rüschendorf conditions to acquire anew function; which supposed to be a density of copula with dependence parameter. According to the evidence, we have got a semicopula function.  Therefore, we can say that a semicopula is a copula function despite of missing increasing property.