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229 results for “regression method”
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Research ArticleOpen accessIn the abstractThe Human Facial Expression Classification Using the Center Kernel Subspace based the Ridge RegressionArif MuntasaThe facial expression classification has been implemented on many devices. However, many researchers have conducted the research to improve the classification rate. This research has developed the algorithm to enhance the classification rate on the facial expression field. The proposed method is divided into five primary processes, which are, the first, create the center kernel subspace-based the ridge regression. Secondly, … …Journal of Computer Science, Vol. 11, Issue 11 · 13 Jan 2016 · 6,803 accessesView PDFCite
Research ArticleOpen accessIn the abstractQuantifying Business Process Optimization using RegressionGezani Richman Miyambu, Solly Matshonisa SeeletseThe paper applies regression methods to model Business Process Optimisation (BPO) in order to derive measures for the extent of BPO achievement if efforts to optimise have already started. This will help to identify components of business that still need to be improved if full optimisation has not yet been achieved in a business. Regression methods were used to explain … …American Journal of Applied Sciences, Vol. 12, Issue 12 · 25 Nov 2015 · 6,629 accessesView PDFCite
Research ArticleOpen accessIn the abstractZero Inflated Poisson and Geographically Weighted Zero- Inflated Poisson Regression Model: Application to Elephantiasis (Filariasis) Counts DataPurhadi, Yuliani Setia Dewi, Luthfatul AmalianaPoisson regression has been widely used for modeling counts data. Violation of equidispersion assumption can occur when there are excess of zeros of the data. For that condition we can use Zero-Inflated Poisson (ZIP) to analyze such data, resulting global parameter estimates. However spatial data from various locations have their own characteristics depend on their socio-cultural, geographical and economic conditions. … …Journal of Mathematics and Statistics, Vol. 11, Issue 2 · 29 Sep 2015 · 8,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm for Variable and Samples Selection in Multivariate Calibration ProblemsKelton de Souza Santiago, Anderson Silva Soares, Telma Woerle de Lima et al.One of the main problems of quantitative analytical chemistry is to estimate the concentration of one or more species from the values of certain physicochemical properties of the system of interest. For this it is necessary to construct a calibration model, i.e., to determine the relationship between measured properties and concentrations. The multivariate calibration is one of the most successful … …Journal of Computer Science, Vol. 11, Issue 4 · 8 Jun 2015 · 7,385 accessesView PDFCite
Research ArticleOpen accessIn the abstractMISSING DATA IMPUTATION USING WEIGHTED OF REGIME SWITCHING MEAN AND REGRESSIONJumlong Vongprasert, Bhusana PremanodeMissing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. The purpose of this work were first to develop the Weighted of Regime Switching Mean and Regression (WRSMRI) for missing data estimation and secondly to compare its efficiency of estimation and statistical power of a … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 3 May 2014 · 6,707 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 · 7,625 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL ROBUST AND EFFICIENT TOOL FOR DETECTING HETEROSCEDASTICITYWei Xiong, Maozai TianOne of the greatest values of Quantile Regression (QR) is that it provides a good procedure in the sense that QR could be much more efficient and sometimes arbitrarily more efficient in recovering the mean function than the Least Squares (LS) even when without moment conditions. However, heteroscedasticity definitely causes conditional variances of parametric or nonparametric estimates of mean functions … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 21 Mar 2014 · 6,662 accessesView PDFCite
Research ArticleOpen accessIn the abstractPOISSON-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 · 7,345 accessesView PDFCite
Research ArticleOpen accessIn the abstractASSESSMENT OF QUALITY OF LIFE IN CANCER PATIENTSFereshteh Farzianpour, Jalil Shojaee, Ghasem Abedi, Farideh RostamiStandards of Joint Commission International (JCI) emphasize on the organizational performance level in basic functional domains including patient right, patient care, medical safety and infection control. These standards are focused on two principles: Expectations of the actual organizational performance and assessment of organizational capabilities to provide high quality and safe Health Care Services (HCS). The aim of this study was … …American Journal of Agricultural and Biological Sciences, Vol. 9, Issue 2 · 9 Jan 2014 · 8,149 accessesView PDFCite
Research ArticleOpen accessIn the abstractAN 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 · 6,819 accessesView PDFCite