Objective: This paper examines and upgrades a two-parameter double exponential distribution to a four-parameter beta double exponential model by compounding the baseline distribution and beta link function to fits and analyse deaths-cases data set of the recent outbreak of the global pandemic coronavirus disease (COVID-19) for both Africa and Non-Africa countries. The new proposed model, although complex in its mathematical structure, yet flexible to implement and its robustness to accommodate non-normal data is an extra advantage to statistical theory and other fields.
Methodology: The statistical properties: the density function, cumulative distribution function, survival function, hazard function, moments, moments generating function, skewness and kurtosis of the developed model were presented. Maximum likelihood method is used for parameters estimation procedure. The new model is validated and compared with some frontier similar extant parametric family of beta distributions using graphs, Kolmogorov Smirnov (KS) Statistic, Log-likelihood and model criteria statistics like Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and Consistent Akaike Information Criteria (CAIC) as tools for comparison.
Results: The graphs, KS, LogL and model criteria statistics values showed that the proposed model fits the COVID-19 pandemic data better than other competing models since the model has lower values as stated: The values from non-African countries KS = 0.1208, LogL = 278.4168, AIC = 560.8336, BIC = 576.1147 and CAIC = 577.1147. Also, from African countries are: KS = 0.0759, LogL = 144.0245, AIC = 292.0490, BIC = 303.9302 and CAIC = 304.9302.
Conclusion: The proposed model showed its applicability and flexibility over other models considered in this work. Therefore, this implies that the new model can be used for modeling other infectious disease data and real data in many fields.
This study examines the daily Road Traffic Crashes (RTC) casualties in Osun state of Nigeria, Comparison of two quality control schemes identified as exponential Weighted Moving Average (EWMA) and Poisson Cumulative sum (CUSUM) control chart techniques were made using data collected from Federal Road Safety Corps (FRSC) Osun-State over a period 120 months our findings revealed that both techniques are capable of detecting small shift from mean level but Cusum is more sensitive. Furthermore, the points of change in the process are clearly identified and easily located on both schemes. The findings provide a proper diagnostic solution in the area of Road Traffic crash (RTC) reduction and control in Osun state Nigeria.
State as a case study. The methodology employed in the analysis of the data collection was chi-square test and descriptive statistics. Important issues raised are that the age range 20-29 has the highest reported cases and based on gender the females have the higher rate of STDs than male as reported in the data collected. live has the highest frequency of 1463 and death with 135 of the reported cases The year with the highest reported cases is 2018 under study. There is no significant difference between life status and year, life status and type of diseases, life status and gender, Life status and age since their p-values are less than 0.05 and accept null hypothesis, while there's a significant difference between age group and gender since the p-value is greater than 0.05 and reject the null hypothesis.
Household surveys collect information on social and demographic characteristics in which the household constitutes the sampling units. They are effective means of obtaining variety of data needed for informed policy formulation and monitoring of national development. Despite their increasing recognition, household surveys suffer from non-response which creates bias estimates leading to wrong inference if not properly addressed. Existing estimators for handling missing values focused on the quality of missing value estimates without considering the resulting effects on location and scale parameters with regard to the nature of missingness and number of missing values. The convoluted weighted method was more efficient than the existing estimators with increasing number and nature of missingness. Its use will enhanced the level of precision of the estimated population parameter in the presence of missing values in household surveys.
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