{"title":"Quasi-likelihood and Quasi-Bayes Estimation in Noncommutative Fractional SPDEs","authors":"Jaya P. N. Bishwal","doi":"10.28924/ada/stat.4.6","DOIUrl":"https://doi.org/10.28924/ada/stat.4.6","url":null,"abstract":"We study the quasi-likelihood and quasi Bayes estimator of the drift parameter in the stochastic partial differential equations when the process is observed at the arrival times of a Poisson process. Unlike the previous work, no commutativity condition is assumed between the operators in the equation. We use a two stage estimation procedure. We first estimate the intensity of the Poisson process. Then we plug-in this estimate in the quasi-likelihood to estimate the drift parameter. Under certain non-degeneracy assumptions on the operators, we obtain the consistency and the asymptotic normality of the estimators.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"333 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140784550","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}
{"title":"New Sine Inverted Exponential Distribution: Properties, Simulation and Application","authors":"I. J. David, S. Mathew, J. Y. Falgore","doi":"10.28924/ada/stat.4.5","DOIUrl":"https://doi.org/10.28924/ada/stat.4.5","url":null,"abstract":"The New Sine Inverted Exponential Distribution, a new distribution model with just one parameter, is suggested in this study. The suggested model has several statistical qualities and reliability properties that have been constructed and explored. The MLE estimations of the parameters were determined using R's adequacy model package. To calculate the bias of the model parameter and the root mean square error, a simulation study was done. The simulation study revealed that the proposed model is well-behaved. The findings also showed that the suggested model outperforms the current listed models on two real datasets when performance was compared.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"18 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140769860","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}
{"title":"Analysis of Students Performance on Admission Placement","authors":"Babagana Modu, Fatima Abdulhamid Yahaya","doi":"10.28924/ada/stat.3.15","DOIUrl":"https://doi.org/10.28924/ada/stat.3.15","url":null,"abstract":"In the present-time, getting admission to study a preferred course of choice in the Nigerian tertiary institutions by prospective applicants is highly competitive. As a criteria, applicants are required to meet the UTME (Unified Tertiary Matriculation Examination (UTME) and five (5) relevant ordinary level credits, including English and Mathematics as a prerequisite before securing admission. However, being wrongly placed for a course that is different from ones choice could negatively affect learning and outcomes. Therefore, proper placement would have tendency of enhancing not only learning and outcomes but also self-esteem; thus improved productivity. This paper has examined students’ performance based on the course sought at entry and course placed to study. The CGPA of 300-Level students in the 2020/2021 session of the Department of Mathematics and Statistics, Yobe State University was used as a particular case for the investigation. Descriptive and Non-parametric techniques were employed. We found that applicants who sought to study computer science or physics at entry but were placed to study mathematics/statistics performed better than those who sought to study chemistry or biology. However, applicants who sought to study chemistry and placed to study mathematics/statistics are fairly better as compared to biology. Conclusively, the results of this study will inform decision makers and tertiary institution managers towards selecting those suitable to study mathematics/statistics if their preferred courses not secured.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135094398","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}
{"title":"Approximate Maximum Likelihood Estimation in Fractional Stochastic Transport Equation","authors":"Jaya P. N. Bishwal","doi":"10.28924/ada/stat.3.14","DOIUrl":"https://doi.org/10.28924/ada/stat.3.14","url":null,"abstract":"We estimate the drift of the fractional stochastic transport equation the by maximum likelihood and the minimum contrast methods. We show consistency and asymptotic normality of the estimators. We consider both continuous and discrete time observations.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135689157","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}
{"title":"Time Series Regression Modeling with AR(1) Errors","authors":"B. Modu, A. Inuwa","doi":"10.28924/ada/stat.3.13","DOIUrl":"https://doi.org/10.28924/ada/stat.3.13","url":null,"abstract":"When ordinary regression analysis is performed using time-series variables, it is common for the errors (residuals) to have a time-series structure. This violates the usual assumption of independent errors in ordinary least squares (OLS) regressions. Consequently, the estimates of the coefficients and their standard errors are incorrect if the time-series structure of the errors is ignored. In this study, an investigation of a regression model with time-series variables, particularly a simple case, was conducted using the conventional method. The ‘AirPassengers Dataset’ was downloaded from the R repository used for the analysis. Ordinary least squares and Cochrane-Orcutt procedures were used as methodologies. The results show that the adjusted regression model with autoregressive errors outperformed the ordinary regression model.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128238925","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}
R. O. Olanrewaju, S. A. Olanrewaju, Serifat Folorunsho, Abibat Gbemisola Dada
{"title":"Time Variant Wave-Signal-Amplitude Trigonometry Regression of Latitudes and Longitudes of the Belmullets of the Atlantic Ocean","authors":"R. O. Olanrewaju, S. A. Olanrewaju, Serifat Folorunsho, Abibat Gbemisola Dada","doi":"10.28924/ada/stat.3.12","DOIUrl":"https://doi.org/10.28924/ada/stat.3.12","url":null,"abstract":"This paper introduces time variant wave-signal-amplitude cosine and sine regression as an extension to wave signal Fourier function and Wave-Shape Function (WSF) model. A full-scale conditional characterization of the linear time variant wave-signal-amplitude cosine and sine model of cosine and sine function with random errors (ηi) was proposed. The associated regression coefficients were estimated via the Ordinary Least Square (OLS) technique, such that, the model wave signal, frequency, and phase were carved-out. In application to real life problem, the wave-signal-amplitude trigonometry model was applied to the real-time observations of the latitude and longitude of the wave buoys’ Belmullets of the Atlantic Ocean. The full-scale real-time observations of the wave climate are the time-variant significant wave height (in metre), peak wave (in oC) and sea temperature (in oC) from 2012 to 2022.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124913457","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}
{"title":"Bernstein-von Mises Theorem and Bayes Estimation in Interacting Particle Systems of Diffusions","authors":"J. Bishwal","doi":"10.28924/ada/stat.3.11","DOIUrl":"https://doi.org/10.28924/ada/stat.3.11","url":null,"abstract":"Consistency and asymptotic normality of the Bayes estimator of the drift coefficient of an interacting particles of diffusions are studied. For the Bayes estimator, observations are taken on a fixed time interval [0, T] and asymptotics are studied in the mean-field limit as the number of interacting particles increases. Interalia, the Bernstein-von Mises theorem concerning the convergence in the mean-field limit of the posterior distribution, for smooth prior distribution and loss function, to normal distribution is proved.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124043982","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}
{"title":"Group Acceptance Sampling Plans for Resubmitted Lots Under Odd Generalized Exponential Log-Logistic Distribution","authors":"D. Sivakumar, K. Kalyani, G. S. Rao, K. Rosaiah","doi":"10.28924/ada/stat.3.9","DOIUrl":"https://doi.org/10.28924/ada/stat.3.9","url":null,"abstract":"In this manuscript, we developed resubmitted lots with group acceptance sampling plan for the lifetime of the product follows the odd generalized exponential log logistic distribution introduced by Rosaiah et al. (2016c). The values of the design parameters of the proposed plan are obtained which are satisfying the both producer’s as well consumer’s risk by fixing the experiment termination time. An application of the proposed plan to the industry is presented and the Kolmogorov-Smirnov test was conducted. However, this plan provides reasonable fit for lifetime of items of ball bearings data. Finally, the advantage of the proposed plan reduces the sample size as compared with the ordinary group sampling scheme. An example is given to illustrate the methodology.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115904358","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}
{"title":"Application of Discriminant Analysis to Predict Students’ Performances in Mathematics in Advanced Secondary Schools","authors":"Nuhu Saidi, G. S. Rao","doi":"10.28924/ada/stat.3.8","DOIUrl":"https://doi.org/10.28924/ada/stat.3.8","url":null,"abstract":"This quantitative study aimed to use discriminant analysis procedures, to develop a classification model to be used for prediction, to predict students’ performances in Mathematics in advanced secondary schools in Tanzania. The study was conducted in Iringa Rural District to model students’ performances in Mathematics in advanced secondary schools owned by the government. Secondary data of students’ performances in Mathematics of 126 students when they were form five in the year 2020/2021 were collected from academic students’ progressive reports and three distinct groups each contained 42 students’ performances were formed. The analysis was done by using R programming software and a seed of 66 was used during the data partitioning to create training and test datasets. The maximum posterior probability rule was used as a classification rule to assign students’ performances in Mathematics into three proposed groups which are: High, Medium and Low. The classification accuracy achieved by the classification model to classify students’ performances in the training dataset is 97.33%. During validation, the model achieved the classification accuracy of 96.08% to classify students’ performances in the test dataset. These findings imply that, the classification model is valid and reliable. Hence the model is convenient to be used for prediction, to predict students’ performances in Mathematics in Advanced Certificate of Secondary Education Examinations.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124705717","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}
{"title":"Statistical Modelling of Road Traffic Accidents: Pattern and Trend in Kogi State, Nigeria","authors":"O. Halid, A. Ilesanmi, T. Oseni","doi":"10.28924/ada/stat.3.7","DOIUrl":"https://doi.org/10.28924/ada/stat.3.7","url":null,"abstract":"Road traffic accident (RTA) is defined as unplanned car crash that causes injuries, fatalities, and property damage. In order to better understand the pattern and trend of road traffic accident in Kogi state, Nigeria, we statistically modeled RTA data collected from Federal Road Safety Corps, Lokoja from January 2017 to December 2021. The data consisted of monthly RTA types and outcomes. The RTA types considered were fatal, serious and minor while the RTA outcomes were death, injury and no injury. Time series modeling was adopted for modeling and predicting the accident rates while Pearson correlation was used to determine the degree of relationship between RTA types and outcomes. Results showed that there were steady fluctuations in the patterns of RTA types and outcomes between February and October while there were upward trend in RTA from November to January. The augmented Dickey-Fuller test showed that RTA series was stationary and out of 10 candidate models obtained using ACF and PACF plots, the best model suitable for forecasting RTA rate was found to be ARIMA(1,0,1) using mean absolute deviation (MAD) and mean square error (MSE) selection criteria. In order to estimate the parameters of the model, the Shapiro-Wilk test was conducted on the RTA values and its residuals to confirm normality. Since p < 0.05 in both cases, they were both found to be non-normal, then the least absolute deviation (LAD) estimator was used for estimation. This gives rise to Yt = 29.0574 + 0.492151Xt-1 + 0.99994et-1 + εt as the best fitted model, which was found to be statistically significant at α=0.05. The estimated model was used to forecast RTA for 30months with 95percent confidence level and result showed that the forecast were good and there will continually be occurrence of RTA nearly every month and there will be higher RTA rates between November and January. The result of the Pearson correlation showed that fatal accident were 71percent more likely associated to death while serious accident were 61percent more likely associated to injury.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129273172","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}