7 articles for “Gaussian or normal distribution”

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Research ArticleOpen accessIn the keywordsPrediction in Complex Dimension Using Kolmogorov's Set of AxiomsAbdo Abou Jaoude, Khaled El-Tawil, Seifedine KadryProblem statement: The five basic axioms of Kolmogorov define the probability in the real set of numbers and do not take into consideration the imaginary part which takes place in the complex set of numbers, a problem that we are facing in many engineering systems. Approach: Evaluate the complex probabilities by considering supplementary new imaginary dimensions to the event occurring … …Journal of Mathematics and Statistics, Vol. 6, Issue 2 · 30 Jun 2010 · 8,519 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMultivariate Option Pricing with Gaussian Mixture Distributions and Mixed CopulasJimbo Henri Claver, Tatanfack Emerson, Shu FelixRecently, it has been reported that the hypothesis proposed by the classical black scholes model to price multivariate options in finance were unrealistic, as such, several other methods have been introduced over the last decades including the copulas methods which uses copulas functions to model the dependence structure of underlying assets. However, the previous work did not take into account … …Journal of Mathematics and Statistics, Vol. 19, Issue 1 · 3 Apr 2023 · 6,511 accessesView PDF Cite

Research ArticleOpen accessIn the abstractTwister Generator of Random Normal Numbers by Box-Muller ModelAleksei F. Deon, Yulian A. MenyaevTwisting generators of the pseudorandom normal variables can use uniform random sequences as a basis. However, such technique could provide poor quality result in cases where the original sequences have insufficient uniformity or skipping of random values. This work offers a new approach for creating the random normal variables using the Box-Muller model as a basis together with the twisting … …Journal of Computer Science, Vol. 16, Issue 1 · 10 Jan 2020 · 11,556 accessesView PDF Cite

Research ArticleOpen accessIn the abstractGAUSSIAN COPULA MARGINAL REGRESSION FOR MODELING EXTREME DATA WITH APPLICATIONSutikno, Heri Kuswanto, Iis Dewi RatihRegression is commonly used to determine the relationship between the response variable and the predictor variable, where the parameters are estimated by Ordinary Least Square (OLS). This method can be used with an assumption that residuals are normally distributed (0, σ2). However, the assumption of normality of the data is often violated due to extreme observations, which are often found … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 4 Apr 2014 · 7,620 accessesView PDF Cite

Research ArticleOpen accessIn the abstractSMOOTHING SPLINE IN SEMIPARAMETRIC ADDITIVE REGRESSION MODEL WITH BAYESIAN APPROACHRita Diana, I. Nyoman Budiantara, Purhadi, Satwiko DarmestoSemiparametric additive regression model is a combination of parametric and nonparametric regression models. The parametric components are not linear but following a polynomial pattern, while the nonparametric components are unknown pattern and assumed to be contained in the Sobolev space. The nonparametric components can be approximated by smoothing spline functions. In the development of smoothing spline, the classical statistical approach … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 12 Jun 2013 · 7,252 accessesView PDF Cite

Research ArticleOpen accessIn the abstractModeling and Forecasting Volatility of the Malaysian Stock MarketsAhmed Shamiri, Zaidi IsaProblem statement: One of the main purposes of modeling variance is forecasting, which is crucial in many areas of finance. Despite the burgeoning interest in and evaluation of volatility forecasts, a clear consensus on witch volatility model/or distribution specification to use has not yet been reached. Therefore, the out of-sample forecasting ability should be a natural model selection criterion for … …Journal of Mathematics and Statistics, Vol. 5, Issue 3 · 30 Sep 2009 · 7,900 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordRisks Ratios of Shrinkage Estimators for the Multivariate Normal MeanAbdenour Hamdaoui, Nadia MezouarWe study the estimation of the mean θ of a multivariate Gaussian random variable X∼Np(θ,σ2Ip) in ℜp, σ2 is unknown and estimated by the chi-square variable S2∼σ2χn2. In this work we are interested in studying bounds and limits of risk ratios of shrinkage estimators to the maximum likelihood estimator X, when n and p tend to infinity. We recall that … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 3 Apr 2017 · 7,108 accessesView PDF Cite