Smoothing-Spline- und Polygonal-Interpolation, Logit-Log- und Logit-Quadrat-Regression: Eine Gegen�berstellung mathematischer Verfahren zur Ergebniswertberechnung von Radioimmunoassays

1976 ◽  
Vol 279 (2) ◽  
pp. 126-127 ◽  
Author(s):  
P. Sandel ◽  
W. Vogt ◽  
B. Popp ◽  
M. Knedel
Keyword(s):  
Smoothing Spline ◽  
Polygonal Interpolation

An improved calibration curve between soil pH measured in waterand CaCl2

Soil Research ◽  
2002 ◽  
Vol 40 (8) ◽  
pp. 1399 ◽  
Author(s):  
B. L. Henderson ◽  
E. N. Bui
Keyword(s):  
Statistical Analysis ◽  
Water Resources ◽  
Soil Ph ◽  
Calibration Curve ◽  
Smooth Function ◽  
Degrees Of Freedom ◽  
Additive Model ◽  
Smoothing Spline ◽  
Look Up Table ◽  
6 Degrees Of Freedom

A new pH water to pH CaCl2 calibration curve was derived from data pooled from 2 National Land and Water Resources Audit projects. A total of 70465 observations with both pH in water and pH in CaCl2 were available for statistical analysis. An additive model for pH in CaCl2 was fitted from a smooth function of pH in water created by a smoothing spline with 6 degrees of freedom. This model appeared stable outside the range of the data and performed well (R2 = 96.2, s = 0.24). The additive model for conversion of pHw to pHCa is sigmoidal over the range of pH 2.5 to 10.5 and is similar in shape to earlier models. Using this new model, a look-up table for converting pHw to pHCa was created.

scholarly journals FUZZY SHRINK IMAGE DENOISING USING SMOOTHING SPLINE ESTIMATION

2014 ◽  
Vol 10 (10) ◽  
pp. 2155-2163
Author(s):  
G.M. Rajathi ◽  
R. Rangarajan ◽  
R. Haripriya ◽  
R. Nithya
Keyword(s):  
Image Denoising ◽  
Smoothing Spline ◽  
Spline Estimation

scholarly journals Speakers’ rapidly-updated expectations influence prosodic realization of information structure

2017 ◽  
Vol 2 ◽  
pp. 51
Author(s):  
Iris Chuoying Ouyang ◽  
Sasha Spala ◽  
Elsi Kaiser
Keyword(s):  
Perspective Taking ◽  
Information Structure ◽  
Smoothing Spline ◽  
Computer Screen ◽  
Interactive Game ◽  
Knowledge State ◽  
Verbal Instructions ◽  
Production Experiment ◽  
Smoothing Spline Anova

A production experiment was conducted to investigate the role of perspective-taking in the prosodic marking of information structure. Participants played an interactive game in which they produced verbal instructions that directed an addressee to place objects in locations on the computer screen. We manipulated (i) the participants’ assumptions about the addressee’s familiarity with the objects and (ii) the addressee’s accuracy in identifying the objects. F0 measurements of the participants’ utterances were analyzed with Smoothing-spline ANOVA models. We find that speakers’ expectations about the addressee’s knowledge state influence the prosodic realization of both new and given information, and that speakers rapidly update their expectations based on the addressee’s behavior during the conversation.

scholarly journals Estimasi Fungsi Regresi Dalam Model Regresi Nonparametrik Birespon Menggunakan Estimator Smoothing Spline dan Estimator Kernel

2018 ◽  
Vol 15 (2) ◽  
pp. 20 ◽  
Author(s):  
Budi Lestari
Keyword(s):  
Regression Model ◽  
Nonparametric Regression ◽  
Kernel Estimator ◽  
Regression Function ◽  
Predictor Variables ◽  
Smoothing Spline ◽  
Estimating Functions ◽  
Nonparametric Regression Model ◽  
Estimation Techniques ◽  
Connection Pattern

Abstract Regression model of bi-respond nonparametric is a regression model which is illustrating of the connection pattern between respond variable and one or more predictor variables, where between first respond and second respond have correlation each other. In this paper, we discuss the estimating functions of regression in regression model of bi-respond nonparametric by using different two estimation techniques, namely, smoothing spline and kernel. This study showed that for using smoothing spline and kernel, the estimator function of regression which has been obtained in observation is a regression linier. In addition, both estimators that are obtained from those two techniques are systematically only different on smoothing matrices. Keywords: kernel estimator, smoothing spline estimator, regression function, bi-respond nonparametric regression model. AbstrakModel regresi nonparametrik birespon adalah suatu model regresi yang menggambarkan pola hubungan antara dua variabel respon dan satu atau beberapa variabel prediktor dimana antara respon pertama dan respon kedua berkorelasi. Dalam makalah ini dibahas estimasi fungsi regresi dalam  model regresi nonparametrik birespon menggunakan dua teknik estimasi yang berbeda, yaitu smoothing spline dan kernel. Hasil studi ini menunjukkan bahwa, baik menggunakan smoothing spline maupun menggunakan kernel, estimator fungsi regresi yang didapatkan merupakan fungsi linier dalam observasi. Selain itu, kedua estimator fungsi regresi yang didapatkan dari kedua teknik estimasi tersebut secara matematis hanya dibedakan oleh matriks penghalusnya.Kata Kunci : Estimator Kernel, Estimator Smoothing Spline, Fungsi Regresi, Model Regresi Nonparametrik Birespon.

Chromatic Confocal Displacement Measurment Based on Correlation Algorithm

2013 ◽  
Vol 446-447 ◽  
pp. 909-914
Author(s):  
Chun Hui Niu ◽  
Yong Lv
Keyword(s):  
Measurement System ◽  
Smoothing Spline ◽  
Peak Wavelength ◽  
Linear Fitting ◽  
Correlation Curve ◽  
Correlation Algorithm ◽  
Spline Fitting ◽  
Fitting Method ◽  
Spectrum Curve ◽  
Confocal Technique

Chromatic confocal technique application in displacement measurement is studied theoretically and experimentally. a set of refractive lenses are designed and a measurement system is established. Correlation fitting method is proposed to fit spectrum curve and find peak wavelength. Results with use of correlation fitting method are compared with Gaussian and smoothing spline fitting methods. It indicate that correlation fitting method have higher extracting accuracy of peak wavelength and smaller RMSE of linear fitting due to narrower and smoother correlation curve.

scholarly journals Smoothing Spline Density Estimation: Theory

1993 ◽  
Vol 21 (1) ◽  
pp. 217-234 ◽  
Author(s):  
Chong Gu ◽  
Chunfu Qiu
Keyword(s):  
Density Estimation ◽  
Estimation Theory ◽  
Smoothing Spline
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