Media Jurnal Penelitian Medika Eksakta Quantity : 7 - Zero. 1 - 2008-04-10 Author : Nur Chámidah
lNFERENSI KURVA REGRESI N0NPARAMETRIK BERDASARKAN ESTIMATOR P0LINOMIAL LOKAL DENGAN Mistake LOGNORMAL Abstrak : Most of statistical analysis data in regression models use normal error assumption, but not really all actual phenomenon gets to the normality assumption. In the most real conditions we usually find lognormal trend, for good examples, call length for each specific of telephone user (Bolotin,1994); response time based on mathematical psychology sights (Breukelen, 1995); non compartmental pharmacokinetic adjustable in some scientific experiments (Lacey et aI, 1997). Eckhard et al., (2001) showed that lognormality sensation can end up being found on the hereditary physic field; on the flower psychology industry, on the meals technology field for instance food handling with distribution procedure and filtering. Chamidah (2004) has done a research of self-confidence interval estimation of nonparametric regression contour with lognormal mistake based on Spline Estimator, Local Polynomial Estimator ánd Kernel Estimator. Thé objectives of this study are to understand the significant shape of the nonparametric regression estimate centered on local polynomial estimator, and produced applications on Software program S-Plus 2000 used to Gmelina Arborea Roxb Shrub data in HTI-Tráns Wanakasita Nusantara Jámbi region. Research results has been an estimated model: with degree of substantial ï.¡=5%, that not all regression coefficients were equal to zero. Thus, the model was substantial with perseverance coefficient (Ur2) 0,9961605. The personal screening of substantial its regression coefficient, i.at the., ï.¢0, ï.¢1 and ï.¢2, with degree of significant ï.¡=5%, and came to the conclusion that all regression coefficient are substantial with the model. On the various other hands, that regional polynomial éstimator in nonparametric régression model with lognormal mistake is appropriate to calculate quantity of Gmelina Arborea Robx bottom on woods diameter.
Keyword : Nonparametric regression, regional polinomial estimator, lognormal mistake
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lNFERENSI KURVA REGRESI N0NPARAMETRIK BERDASARKAN ESTIMATOR P0LINOMIAL LOKAL DENGAN Mistake LOGNORMAL Abstrak : Most of statistical analysis data in regression models use normal error assumption, but not really all actual phenomenon gets to the normality assumption. In the most real conditions we usually find lognormal trend, for good examples, call length for each specific of telephone user (Bolotin,1994); response time based on mathematical psychology sights (Breukelen, 1995); non compartmental pharmacokinetic adjustable in some scientific experiments (Lacey et aI, 1997). Eckhard et al., (2001) showed that lognormality sensation can end up being found on the hereditary physic field; on the flower psychology industry, on the meals technology field for instance food handling with distribution procedure and filtering. Chamidah (2004) has done a research of self-confidence interval estimation of nonparametric regression contour with lognormal mistake based on Spline Estimator, Local Polynomial Estimator ánd Kernel Estimator. Thé objectives of this study are to understand the significant shape of the nonparametric regression estimate centered on local polynomial estimator, and produced applications on Software program S-Plus 2000 used to Gmelina Arborea Roxb Shrub data in HTI-Tráns Wanakasita Nusantara Jámbi region. Research results has been an estimated model: with degree of substantial ï.¡=5%, that not all regression coefficients were equal to zero. Thus, the model was substantial with perseverance coefficient (Ur2) 0,9961605. The personal screening of substantial its regression coefficient, i.at the., ï.¢0, ï.¢1 and ï.¢2, with degree of significant ï.¡=5%, and came to the conclusion that all regression coefficient are substantial with the model. On the various other hands, that regional polynomial éstimator in nonparametric régression model with lognormal mistake is appropriate to calculate quantity of Gmelina Arborea Robx bottom on woods diameter.
Keyword : Nonparametric regression, regional polinomial estimator, lognormal mistake
Web page 1
Pengantar Statistik Inferensial. Muhammad Jainuri. Download with Google Download with Facebook or download with email. Pengantar Statistik Inferensial. Dan mensyaratkan data harus berdistribusi normal, homogen, linear dan data random sampling. Ukuran uji dalam statistik parametrik antara lain: T-test Anova Regresi Korelasi.