European Journal of Statistics最新文献

{"title":"Hypotheses Testing in Nonergodic Fractional Ornstein-Uhlenbeck Models","authors":"J. Bishwal","doi":"10.28924/ada/stat.3.6","DOIUrl":"https://doi.org/10.28924/ada/stat.3.6","url":null,"abstract":"We obtain explicit form of fine large deviation theorems for the log-likelihood ratio in testing models with fractional nonergodic Ornstein-Uhlenbeck processes with Hurst parameter more than half and get explicit rates of decrease of the error probabilities of Neyman-Pearson, Bayes and minimax tests.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124904251","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":"The Impact of Global Financial Crisis and COVID-19 Pandemic on Crude Oil Futures Returns","authors":"Monday Osagie Adenomon, Ngozi G. Emenogu, R. Idowu","doi":"10.28924/ada/stat.3.5","DOIUrl":"https://doi.org/10.28924/ada/stat.3.5","url":null,"abstract":"This study investigates the impact of the global financial crisis and of the present COVID-19 pandemic on daily and weekly Crude oil futures using four variants of ARMA-GARCH models: ARMA-sGARCH, ARMA-eGARCH, ARMA-TGARCH and ARMA- aPARCH with dummy variables We also investigated the persistence, half-life and backtesting of the models. This study therefore seeks to contribute to the body of literature on the impact of the global financial crisis and the present COVID-19 pandemic on the crude oil futures market. The impact of the global financial crisis and the COVID-19 on the crude oil futures has not been investigated at present. We obtained and analyzed the daily and weekly crude oil futures from secondary sources. The daily crude oil futures used in this study cover the period from 4th January 2000 to 27th April 2020 while the weekly crude oil futures covered the period from 2nd January 2000 to 26th April 2020. The global financial crisis period covered the period from 2nd July 2007 to 31st March 2009 and the current COVID-19 pandemic covered the period from 1st January 2020 to 27th April, 2020.  The study used both Student t and skewed Student t innovations with AIC, goodness-of-test fit and backtesting to select the best model.  Most of the estimated ARMA-GARCH models are supported by skewed Student t distribution while most of the ARMA-GARCH models exhibited high persistence values in the presence of the global financial crisis and the COVID-19 pandemic. In the overall, the estimated ARMA(1,0)-eGARCH(2,1) and ARMA(1,0)-eGARCH(2,2) model for daily crude oil futures and weekly crude oil futures respectively have been significantly impacted by the global financial crisis and the Present COVID-19 pandemic while the preferred estimated models also passed the goodness-of-test fit and backtesting. This study recommends shareholders and investors should think outside the box as crude oil futures tend to be affected by the global financial crisis and COVID-19 pandemic while countries also that depend mostly on crude oil are encouraged to diversify their economy in order to survive and be sustained during the financial and health crisis.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115662128","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":"A Variable Step Size Multi-Block Backward Differentiation Formula for Solving Stiff Initial Value Problem of Ordinary Differential Equations","authors":"A. Sagir, M. Abdullahi","doi":"10.28924/ada/stat.3.4","DOIUrl":"https://doi.org/10.28924/ada/stat.3.4","url":null,"abstract":"A variable step size multi-block backward differentiation formula for solving stiff initial value problems of ordinary differential equations with a variable step size strategy was derived. The proposed method (VSSMBBDF) computes two approximate solution values at a time per integration step. The stability properties are achieved by varying the step size ratio in the formula to generate more zero stable schemes. The proposed method is also found to be an A-Stable scheme across different choices of the step size. The method is capable of solving stiff IVPs of ODEs. Approximates result from the system of stiff ODE problems considered are found to favorably validate the performance of the new method in terms of accuracy of the scale error and less executional time in respect to the two methods compared in the study. Hence, the proposed method can be an alternative solver for stiff IVPs of ODEs.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127814909","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":"Moment Properties of Generalized Order Statistics Based on Modified Weighted Rayleigh Distribution","authors":"Haseeb Athar, Mohamad A. Fawzy, Yousef F. Alharbi","doi":"10.28924/ada/stat.3.1","DOIUrl":"https://doi.org/10.28924/ada/stat.3.1","url":null,"abstract":"The generalized order statistics is a unified model of several ordered random schemes such as order statistics, record values, progressive type II right censored order statistics, etc. Order statistics and record values appear in many statistical applications and are widely used in statistical modeling and inference. Progressive Type-II censored sampling scheme is a versatile censoring scheme because it allows the experimenter to save time and cost of the life-testing experiment and is quite useful in reliability and lifetime studies. Rayleigh distribution and its extended version such as modified weighted Rayleigh distribution are important distributions for modeling lifetime data in reliability analysis and engineering science. In this paper, we studied moment properties of generalized order statistics from modified weighted Rayleigh distribution. Further, characterization results based on moment properties and conditional expectation are presented. The simulation studies based on order statistics, upper record values, and progressive type II right censored order statistics are also carried out.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127710109","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":"Liable Characteristics Measure and Anticipate the Diabetes Disease Using Machine Learning Tools","authors":"M. M. Hossain, Md. Rana Ahmed, M. Hasan, M. Sultana, K. Fatema","doi":"10.28924/ada/stat.3.2","DOIUrl":"https://doi.org/10.28924/ada/stat.3.2","url":null,"abstract":"Diabetes is a cardiovascular disease. It is not only an epidemic in Bangladesh but also in the whole world that is increasing rapidly. At an early period of human life, machine learning techniques are used to predict diabetes datasets. In our research paper, we use the Pima diabetes dataset from the Kaggle UCI machine learning data repository. For diabetic patients and doctors, machine learning techniques are both cost-effective and time-saving. We apply KNN, Nave Bayes, Random forest, Support vector machine, Simple logistic, and J48 to Pima datasets. Besides these algorithms, we may develop an ensemble (Vote) hybrid model with WEKA software by combining individual methods that provide the best performance and accuracy. Also, try to make a comparison among all machine learning tool’s accuracy and performance with the proposed ensemble model.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125107280","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":"MLE Evolution Equation for Fractional Diffusions and Berry-Esseen Inequality of Stochastic Gradient Descent Algorithm for American Option","authors":"J. Bishwal","doi":"10.28924/ada/stat.2.13","DOIUrl":"https://doi.org/10.28924/ada/stat.2.13","url":null,"abstract":"We study recursive parameter estimation in fractional diffusion processes. First, stability and asymptotic properties of the global maximum likelihood estimator (MLE) of the drift parameter are obtained under some regularity conditions. Then we obtain an evolution equation for the MLE of the drift parameter in nonhomogeneous fractional stochastic differential equation (fSDE) driven by fractional Brownian motion. This equation is then modified to yield an algorithm which is consistent, asymptotically efficient and converges to the MLE. The gradient and Newton type algorithm are firstorder approximations. Finally we study the Berry-Esseen inequality for stochastic gradient descent in continuous time (SGDCT) algorithm for American option. We compare it with Longstaff-Schwartz regression based method.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125222206","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":"Testing Fixed and Random Terms in Linear Mixed Models","authors":"Marco Barnabani","doi":"10.28924/ada/stat.2.12","DOIUrl":"https://doi.org/10.28924/ada/stat.2.12","url":null,"abstract":"In linear mixed models the selection of fixed and random effects using a testing hypothesis approach brings up several problems. We deal with the boundary point problem emerging when no randomness is hypotesized and the confounding impact of randomness on the coefficients arising when fixed effects are tested. The test statistics are defined by a ratio of two quadratic forms derived from ordinary least squares, are simple, sufficiently general, easy to compute, with known finite sample properties. The test statistic on randomness has a known exact distribution, the density of the statistic on fixed effect is unknown and is approximated by a noncentral F−distribution. The goodness-of-approximation and the selection approach is examined in-depth by simulation. The method proposed in this paper must be seen as complementary to existing selection procedures widening and enriching all information necessary for taking a decision.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121221924","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":"Evaluating Pairwise Variable Selection Methods","authors":"E. Reschenhofer","doi":"10.28924/ada/stat.2.11","DOIUrl":"https://doi.org/10.28924/ada/stat.2.11","url":null,"abstract":"This paper discusses novel methods for the pairwise selection of explanatory variables from a large set of candidate pairs. These methods are applied to monthly time series of surface temperature and their performance is compared with that of conventional selection criteria such as AIC and BIC. In our frequency-domain analysis of the temperature datasets, the pairs are defined in a natural way as cosine and sine vectors of the same frequency. The results show that the new criteria are the only ones which are able to correctly identify seasonal patterns.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"379 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115173546","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":"Inverse Two-Parameter Lindley Distribution and Its Applications","authors":"Chisimkwuo John","doi":"10.28924/ada/stat.2.10","DOIUrl":"https://doi.org/10.28924/ada/stat.2.10","url":null,"abstract":"This paper proposes an Inverse two-parameter Lindley distribution (ITPLD). This is originated from Lindley distribution and two-parameter Lindley distribution. Its mathematical and statistical properties which includes its survival function, hazard rate function, shape characteristics of the density, stochastic ordering, entropy measure, and stress-strength reliability were discussed. The estimation of parameters was carried out using the method of maximum likelihood. Also, in the application of the model, HQIC, BIC, CAIC, AIC, and K.S are used to test for the goodness of fit of the model which was applied to two real data sets. The Inverse two-parameter Lindley distribution was compared with Inverse Lindley, Inverse Akash, and Inverse Exponential distributions in order to determine its superiority.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114401706","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":"Efficiency of Financial Ratios in Predicting Stock Price Trends of Listed Banks at Nairobi Securities Exchange","authors":"M. A. Jallow, Nafiu Lukman Abiodun, P. Weke, Cherif Ahmat Tidiane Aidara","doi":"10.28924/ada/stat.2.9","DOIUrl":"https://doi.org/10.28924/ada/stat.2.9","url":null,"abstract":"In this paper, we examined financial ratios and their effects in predicting stock price trends of listed banks at Nairobi Securities Exchange for the period 2019. Valuation and Profitability ratios are used to measure the value of firms and to investigate whether financial ratios have an effect on Stock Prices of the firms or not. This is investigated using multiple linear regression analysis step-wise method with P/E ratio, P/CF ratio, P/S ratio, P/B ratio, Return on Equity and Dividend Yield as the independent variables and stock prices of the firms as the dependent variables. The results of this study show that all the six financial ratios have a significant effect on stock prices. Besides, price-to-earning ratio, price-to-cash flow ratio, price-to-book ratio and return on equity have a higher correlation with stock price of the firms than other ratios. On the basis of these findings, the study concludes that I & M Holdings limited qualifies to perform better as an undervalue company in the year 2019 and companies need to pay more attention on financial ratios, and that there is increasing need for a more credible and comprehensive disclosure of financial ratios in the annual reports of firms.","PeriodicalId":153849,"journal":{"name":"European Journal of Statistics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123918878","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}