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22 results for “univariate model”
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Research ArticleOpen accessPhrase in the titleSpecification of the Outlier Univariate ModelN. P. OlewueziProblem statement: An outlier is an observation that deviates so much from other observations so as to arouse suspicion that it was generated by a different mechanism. Approach: In this study, outlier univariate model was specified based on statistical measures, Outlier Free (OF) and Outlier Contaminated (OC) models were Stated and compared. Results: The number of expected outliers obtained and … …Journal of Mathematics and Statistics, Vol. 7, Issue 4 · 3 Nov 2011 · 6,905 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleUnivariate Generalized Additive Models for Simulated Stationary and Non-Stationary Generalized Pareto DistributionMostafa Behzadi, Mohd Bakri Adam, Anwar FitriantoGeneralized additive models as a predictor in regression approaches, are made up over cubic spline basis and penalized regression splines. Despite of linear predictor in GLM, generalized additive models use a sum of smooth functions of covariates as a predictor. The data which are used in this study have generalized Pareto distribution and have been simulated by inversion method. The … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 3 Jun 2017 · 7,430 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleForecasting Foreign Direct Investment Inflow in Jordan: Univariate ARIMA ModelAl-Abdulrazag Bashier, Bataineh TalalThe present study is an attempt to build a Univariate time series model to forecast the FDI inflows into Jordan over the coming period 2004-2025. The study employs Box-Jenkins methodology of building ARIMA (Autoregressive Integrated Moving Average) model to achieve the goals of the study. An annual sample time series data for the FDI in Jordan was utilized over the … …Journal of Social Sciences, Vol. 3, Issue 1 · 31 Mar 2007 · 8,385 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePOISSON-WEIGHTED EXPONENTIAL UNIVARIATE VERSION AND REGRESSION MODEL WITH APPLICATIONSHossein Zamani, Noriszura Ismail, Pouya FaroughiThis study introduces a new two-parameter mixed Poisson distribution, namely Poisson-Weighted Exponential (P-WE), which is obtained by mixing Poisson distribution with a new class of weighted exponential distribution. The new P-WE distribution provides a more flexible alternative for modelling over dispersed count data compared to Poisson distribution. The estimation procedures of P-WE distribution via method of moments and maximum likelihood … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 8 Mar 2014 · 7,341 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Lifetime Data Modeling With the Modified Version of Weibull Distribution: A Comparative ApproachArjun Kumar Gaire, Shahid Mohammad, Yogendra Bahadur GurungThis study introduces a new two-parameter univariate distribution, a modified version of the Weibull distribution, for a non-negative realm. Originating from a framework introduced by Azzalini and Capitanio, the distribution exhibits a monotonically increasing hazard rate. It offers closed-form expressions for key statistical properties, including reliability functions, moments, moment-generating functions, and order statistics. An expression for random number generation is … …Journal of Mathematics and Statistics, Vol. 21, Issue 1 · 8 Oct 2025 · 3,085 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Artificial Neural Network Point Forecasting Models and Prediction Intervals for Solar Irradiance EstimationAntônio Fabrício Guimarães de Sousa, Helaine Cristina Moraes Furtado, Wilson Negrão Macêdo, Anderson Alvarenga de Moura MenesesAn accurate knowledge on solar irradiance prediction is particularly required for proper development and planning of Photovoltaic (PV) energy systems. The main purpose of the present research is to assess the accuracy of Artificial Neural Networks (ANN) short-term forecast of univariate solar irradiance time series, with conventional point prediction and Prediction Intervals (PIs), comparing models. The Lower Upper Bound Estimation … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 3 · 17 Jul 2020 · 7,440 accessesView PDFCite
Review ArticleOpen accessIn the abstractArtificial Intelligence Techniques and External Factors used in Crime Forecasting in Violence and Property: A ReviewRebaz Mala Nabi, Soran Ab. M. Saeed, Habibollah HaronCrime forecasting is beneficial in providing useful information to authorities in planning effective crime prevention measures. The two types of analysis used in crime forecasting are univariate and multivariate. Comparatively, multivariate analysis provides better forecasting accuracy because of its ability to discover crime patterns not previously seen. Crime is strongly influenced by several external factors, including economic, social and demographic. … …Journal of Computer Science, Vol. 16, Issue 2 · 19 Feb 2020 · 7,918 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Convergence Theorem for Bivariate Exponential Dispersion ModelsLila Ricci, Gabriela BoggioMultivariate exponential dispersion models (MEDMs) were defined in 2013 by Jørgensen and Martínez. A particular case of MEDM is the bivariate Gamma model; in this article we prove that, under certain conditions, this is a limit distribution for MEDM generated by bivariate regularly varying measures, extending a previous result given by the aforementioned authors for the univariate case. As necessary … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 25 Jul 2019 · 6,582 accessesView PDFCite
Case ReportOpen accessIn the abstractEvaluation of Seasonal Autoregressive Integrated Moving Average Models for River Flow ForecastingKassahun Birhanu Tadesse, Megersa Olumana Dinka, Tena Alamirew, Semu Ayalew MogesReservoir operation policies cannot be functional in instant decision making without forecasting the future reservoir inflows. For forecasting inflows into reservoirs with only hydrological data is available like Koga irrigation dam, multivariate forecasting models cannot be used to generate accurate river flow information. As a result, an evaluation of univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) models was done for … …American Journal of Environmental Sciences, Vol. 13, Issue 5 · 28 Sep 2017 · 7,885 accessesView PDFCite