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Mass media Jurnal Penelitian Medika Eksakta Volume : 7 - No. 1 - 2008-04-10 Writer : Nur Chámidah
lNFERENSI KURVA REGRESI N0NPARAMETRIK BERDASARKAN ESTIMATOR P0LINOMIAL LOKAL DENGAN ERROR LOGNORMAL Abstrak : Most of record analysis information in regression models use normal error presumption, but not really all genuine phenomenon reaches the normality presumption. In the most real situations we usually find lognormal phenomenon, for good examples, call length of time for each specific of phone user (Bolotin,1994); reaction time structured on numerical psychology sights (Breukelen, 1995); non compartmental pharmacokinetic adjustable in some clinical experiments (Lacey et aI, 1997). Eckhard et al., (2001) demonstrated that lognormality sensation can be found on the hereditary physic industry; on the herb psychology field, on the foods technology field for example food developing with dispersion process and filtering. Chamidah (2004) has completed a research of self-confidence interval estimate of nonparametric regression contour with lognormal mistake centered on Spline Estimator, Nearby Polynomial Estimator ánd Kernel Estimator. Thé objectives of this study are usually to understand the significant contour of the nonparametric regression estimate structured on regional polynomial estimator, and produced programs on Software program S-Plus 2000 applied to Gmelina Arborea Roxb Woods data in HTI-Tráns Wanakasita Nusantara Jámbi area. Research results has been an estimated design: with level of substantial ï.¡=5%, that not really all regression coefficients were equivalent to zero. Consequently, the design was substantial with dedication coefficient (R2) 0,9961605. The specific testing of significant its regression coefficient, i.age., ï.¢0, ï.¢1 and ï.¢2, with level of significant ï.¡=5%, and deducted that all regression coefficient are usually significant with the design. On the various other hands, that nearby polynomial éstimator in nonparametric régression design with lognormal error is suitable to estimate quantity of Gmelina Arborea Robx base on woods size.
Keyword : Nonparametric regression, regional polinomial estimator, lognormal error
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lNFERENSI KURVA REGRESI N0NPARAMETRIK BERDASARKAN ESTIMATOR P0LINOMIAL LOKAL DENGAN ERROR LOGNORMAL Abstrak : Most of record analysis information in regression models use normal error presumption, but not really all genuine phenomenon reaches the normality presumption. In the most real situations we usually find lognormal phenomenon, for good examples, call length of time for each specific of phone user (Bolotin,1994); reaction time structured on numerical psychology sights (Breukelen, 1995); non compartmental pharmacokinetic adjustable in some clinical experiments (Lacey et aI, 1997). Eckhard et al., (2001) demonstrated that lognormality sensation can be found on the hereditary physic industry; on the herb psychology field, on the foods technology field for example food developing with dispersion process and filtering. Chamidah (2004) has completed a research of self-confidence interval estimate of nonparametric regression contour with lognormal mistake centered on Spline Estimator, Nearby Polynomial Estimator ánd Kernel Estimator. Thé objectives of this study are usually to understand the significant contour of the nonparametric regression estimate structured on regional polynomial estimator, and produced programs on Software program S-Plus 2000 applied to Gmelina Arborea Roxb Woods data in HTI-Tráns Wanakasita Nusantara Jámbi area. Research results has been an estimated design: with level of substantial ï.¡=5%, that not really all regression coefficients were equivalent to zero. Consequently, the design was substantial with dedication coefficient (R2) 0,9961605. The specific testing of significant its regression coefficient, i.age., ï.¢0, ï.¢1 and ï.¢2, with level of significant ï.¡=5%, and deducted that all regression coefficient are usually significant with the design. On the various other hands, that nearby polynomial éstimator in nonparametric régression design with lognormal error is suitable to estimate quantity of Gmelina Arborea Robx base on woods size.
Keyword : Nonparametric regression, regional polinomial estimator, lognormal error
Page 1