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573 results for “regression”
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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 accessEvery word in the titleMAPPING OF ILLITERACY AND INFORMATION AND COMMUNICATION TECHNOLOGY INDICATORS USING GEOGRAPHICALLY WEIGHTED REGRESSIONRokhana Dwi Bekti, Andiyono, Edy IrwansyahGeographically Weighted Regression (GWR) is a technique that brings the framework of a simple regression model into a weighted regression model. Each parameter in this model is calculated at each point geographical location. The significantly parameter can be used for mapping. In this research GWR model use for mapping Information and Communication Technology (ICT) indicators which influence on illiteracy. This … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 21 Feb 2014 · 7,096 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAN EFFECTIVE TECHNIQUE OF MULTIPLE IMPUTATION IN NONPARAMETRIC QUANTILE REGRESSIONYanan Hu, Qianqian Zhu, Maozai TianIn this study, we consider the nonparametric quantile regression model with the covariates Missing at Random (MAR). Multiple imputation is becoming an increasingly popular approach for analyzing missing data, which combined with quantile regression is not well-developed. We propose an effective and accurate two-stage multiple imputation method for the model based on the quantile regression, which consists of initial imputation … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 4 Jan 2014 · 6,813 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePERFORMANCE OF RIDGE REGRESSION ESTIMATOR METHODS ON SMALL SAMPLE SIZE BY VARYING CORRELATION COEFFICIENTS: A SIMULATION STUDYAnwar Fitrianto, Lee Ceng YikWhen independent variables have high linear correlation in a multiple linear regression model, we can have wrong analysis. It happens if we do the multiple linear regression analysis based on common Ordinary Least Squares (OLS) method. In this situation, we are suggested to use ridge regression estimator. We conduct some simulation study to compare the performance of ridge regression estimator … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 3 Jan 2014 · 8,540 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleGENERALIZED REGRESSION NEURAL NETWORK BASED EXPERT SYSTEM FOR HEPATITIS B DIAGNOSISC. Mahesh, E. Kannan, M. S. SaravananHepatitis B is a potentially life-threatening liver infection caused by the hepatitis B virus. The virus interferes with the function of the liver while replicating in hepatocytes. It is a major global health problem and the most serious type of viral hepatitis. Chronic liver disease is caused by viral hepatitis and putting people at high risk of death from cirrhosis … …Journal of Computer Science, Vol. 10, Issue 4 · 3 Dec 2013 · 6,983 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleESTIMATION OF CLAIM COST DATA USING ZERO ADJUSTED GAMMA AND INVERSE GAUSSIAN REGRESSION MODELSYulia Resti, Noriszura Ismail, Saiful Hafizah JamaanIn actuarial and insurance literatures, several researchers suggested generalized linear regression models (GLM) for modeling claim costs as a function of risk factors. The modeling of claim costs involving both zero and positive claims experience has been carried out by fitting the claim costs collectively using Tweedie model. However, the probability of zero claims in Tweedie model is not allowed … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 11 Jul 2013 · 7,263 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSMOOTHING 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 accessEvery word in the titleEffective Test Case Selection and Prioritization in Regression TestingAlbert Pravin, Subramaniam SrinivasanRegression testing is used to ensure the validity of the changed software. Due to time budget and entire test suite could not be executed. Hence it becomes an essential to minimize the test suite and choose a subset of test cases from test suite which will be executed in least time and has the capability to cover all the faults. … …Journal of Computer Science, Vol. 9, Issue 5 · 28 May 2013 · 7,140 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePartial Least Squares Regression Based Variables Selection for Water Level PredictionsNoraini Ibrahim, Antoni WibowoFloods are common phenomenon in the state of Kuala Krai, specifically in Kelantan-Malaysia. Every year, floods affecting biodiversity on this region and also causing property loss of this residential area. The residents in Kelantan always suffered from floods since the water overflows to the areas adjoining to the rivers, lakes or dams. Months, average monthly rainfall, temperature, relative humidity and … …American Journal of Applied Sciences, Vol. 10, Issue 4 · 7 Apr 2013 · 6,621 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOn Multiresponse Semiparametric Regression ModelSri Haryatmi, I. Nyoman Budiantara, Wahyu WibowoThe modeling between predictors and response in statistics sometimes deals with more than one response or multiresponse situation. Furthermore, it can be happen that some predictors have linear relationship with the responses and the others predictor have unknown relationship. To overcome this modeling problem we proposed multiresponse semiparametric regression model. This model has more than one response and contains both … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 20 Feb 2013 · 7,068 accessesView PDFCite