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Toplam kayıt 22, listelenen: 1-10
Estimation of Clearness Index Model Via Crs, Tprs and Mars
(Isoss Publ, 2011)
Nonparametric approach is more flexible than parametric approach in assuming that f belongs to a smooth family of functions. Hence, a nonparametric approach does not require an assumption of linearity. Based on our motivating ...
Estimation of clearness index model via CRS, TPRS and mars
(2011)
Nonparametric approach is more flexible than parametric approach in assuming that f belongs to a smooth family of functions. Hence, a nonparametric approach does not require an assumption of linearity. Based on our motivating ...
The individuals control charts for burr distributed and Weibull distributed data
(2006)
Constructing the control limits supposes the assumption of the normality. However, there are numerous studies on the control charts when the underlying distribution is non-normal. Several authors have investigated the ...
Analysis of international debt problem using artificial neural networks and statistical methods
(Springer, 2010)
It is known from the scientific researches that artificial neural networks are alternatives of statistical methods such as regression analysis and classification in recent years. Since multi-layer backpropagation neural ...
Comparison of goodness-of-fit measures in probit regression model
(Taylor & Francis Inc, 2007)
This article examines several goodness-of-fit measures in the binary probit regression model. Existing pseudo-R-2 measures are reviewed, two modified and one new pseudo-R-2 measure are proposed. For the probit regression ...
Variable selection with genetic algorithm and multivariate adaptive regression splines in the presence of multicollinearity
(Inst Advanced Science Extension, 2016)
In this paper, it is aimed to determine the true regressors explaining the dependent variable in multiple linear regression models and also to find the best model by using two different approaches in the presence of low, ...
Robust ridge and robust Liu estimator for regression based on the LTS estimator
(Taylor & Francis LTD, 2013)
In the multiple linear regression analysis, the ridge regression estimator and the Liu estimator are often used to address multicollinearity. Besides multicollinearity, outliers are also a problem in the multiple linear ...
Modi?ed tests for comparison of group means under heteroskedasticity and non-normality caused by outlier(s)
(2017)
There are several approximate tests proposed such as Welch's F-test (W), the Parametric Bootstrap Test (PB) and Generalized F-test (GF) for comparing several group means under heteroskedasticity. These tests are powerful ...
Modelling Extreme Rainfalls Using Generalized Additive Models for Location, Scale and Shape Parameters
(Corvinus University Budapest, 2016)
This study aims to model the nonlinear relationship between the daily amount of extreme rainfall and significant predictor variables by the Generalized additive models for location, scale and shape parameters (GAMLSS). ...
Statistical methods and artificial neural networks
(2006)
Artificial Neural Networks and statistical methods are applied on real data sets for forecasting, classification, and clustering problems. Hybrid models for two components are examined on different data sets; tourist arrival ...