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25 results for “Gaussian distribution”

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Research ArticleOpen accessIn the abstractAccessing the Appropriateness of a Spatial Regression Using Generalized (h1h2-)Slepian Random FieldWayan Somayasa, Jamhir Safani, La Ode Ngkoimani, Muhamad Zamrun F.In this study we derived asymptotic goodness-of-fit test (model check) for spatial regression where the critical region as well as the p-value of the tests are approximated based on the distribution of a type of the integral functional of the generalized (h1h2-)-Slepian field and the set-indexed Gaussian white noise. Such random fields are obtained as the limit process of the … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 2 May 2017 · 7,362 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvergence of Renormalization Group Transformations of Gibbs Random FieldFarida Kachapova, Ilias KachapovStatistical mechanics describes interaction between particles of a physical system. Particle properties of the system can be modelled with a random field on a lattice and studied at different distance scales using renormalization group transformation. Here we consider a thermodynamic limit of a lattice model with weak interaction and we use semi-invariants to prove that random fields transformed by renormalization … …Journal of Mathematics and Statistics, Vol. 12, Issue 3 · 27 Jul 2016 · 7,012 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Joint Degree Distribution (JDD) in Luby Transform CodesI. Joe Louis Paul, S. Radha, J. RajaLuby Transform (LT) codes, the first realization of rateless codes are widely used in wireless communication mainly for its adaptability to varying channel conditions and its capacity approaching performance. In spite of the above advantages and its simplicity in implementation, LT codes suffer from a bottle neck of premature termination due to the poor design of degree distribution. In this … …Journal of Computer Science, Vol. 11, Issue 1 · 13 Aug 2014 · 7,258 accessesView PDFCite
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 PDFCite
Research ArticleOpen accessIn the abstractA COMPARISION OF VARIOUS EDGE DETECTION TECHNIQUES IN MOTION PICTURE FOR IDENTIFYING A SHARK FISHShrivakshan Gopal Thiruvangadan, Chelliah ChandrasekarThe significant feature of detecting the motion image objects in this study it try identify the shark fish videos by removing the Background of the image. The main method involved in the detecting from the background is the foreground detection of the image. There are many techniques which usually ignore the fact that the background images consist of different image … …Journal of Computer Science, Vol. 9, Issue 11 · 18 Sep 2013 · 6,691 accessesView PDFCite
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 PDFCite
Research ArticleOpen accessIn the abstractA Novel Algorithmic Cost Estimation Model Based on Soft Computing TechniqueIman Attarzadeh, Siew Hock OwProblem statement: Software development effort estimation is the process of predicting the most realistic use of effort required for developing software based on some parameters. It has always characterized one of the biggest challenges in Computer Science for the last decades. Because time and cost estimate at the early stages of the software development are the most difficult to obtain … …Journal of Computer Science, Vol. 6, Issue 2 · 28 Feb 2010 · 7,927 accessesView PDFCite
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 PDFCite
Research ArticleOpen accessIn the abstractGeneral Properties of 3/2ω0 and 2ω0 Harmonics Emission from Laser Driven PlasmasA.S.A. Dib, A.H. BelbachirUsing a simple model based on the conversion of electron plasma waves into electromagnetic waves through a process of parametric interaction of four waves, the general properties of the 3/2ω0 emission and the 2ω0 emission generated by the interaction of a Gaussian laser pulse with homogeneous plasma are studied. Some known characteristics of these emissions are reproduced within this model … …American Journal of Applied Sciences, Vol. 5, Issue 8 · 31 Aug 2008 · 6,502 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Gaussianity Evaluations of Malaysian Stock Return VolatilityChin Wen CheongWe study the distribution of standardized returns by using various frequencies data. The empirical standardized returns are obtained by using the unobserved and observable daily volatility. Our empirical results evidence the realized-standardized returns follow nearest to a Gaussian distribution. On the other hand, the standardized returns using daily closing and range-based data are able to reduce but not fully eliminate … …American Journal of Applied Sciences, Vol. 5, Issue 2 · 28 Feb 2008 · 7,078 accessesView PDFCite