reference curves are useful tools to monitor children’s growth status and can promote growth velocity in infants. in this regard, various parametric and semi-parametric methods are frequently used in the last decades. in the present paper, nonparametric quintile regression method is used as a powerful and applicable methodology to estimate height curves and normal values of height-for-age in ch...

We compare parametric and nonparametric estimation methods in the context of PBPK modeling using simulation studies. We implement a Monte Carlo Markov Chain simulation technique in the parametric method, and a functional analytical approach to estimate the probability distribution function directly in the nonparametric method. The simulation results suggest an advantage for the parametric metho...

Parametric images generated from dynamic positron emission tomography (PET) studies are useful for presenting functional/biological information in the 3-dimensional space, but usually suffer from their high sensitivity to image noise. To improve the quality of these images, we proposed in this study a modified linear least square (LLS) fitting method named cLLS that incorporates a clustering-ba...

A new method for determining knots in parametric curve interpolation is presented. The determined knots have a quadratic polynomial precision in the sense that an interpolation scheme which reproduces quadratic polynomials would reproduce parametric quadratic polynomials if the new method is used to determine knots in the interpolation process. Testing results on the efficiency of the new metho...

A new orthogonal projection method for computing the minimum distance between a point and a spatial parametric curve is presented. It consists of a geometric iteration which converges faster than the existing Newton’s method, and it is insensitive to the choice of initial values. We prove that projecting a point onto a spatial parametric curve under the method is globally second-order convergence.

In this paper, the author designs an efficient method for imputing iteratively missing target values with semiparametric kernel regression imputation, known as the semi-parametric iterative imputation algorithm (SIIA). While there is little prior knowledge on the datasets, the proposed iterative imputation method, which impute each missing value several times until the algorithms converges in e...

This paper describes the comparison of the anova and the KruskalWallis test by means of the power when violating the assumption about normally distributed populations. The permutation method is used as a simulation method to determine the power of the test. It appears that in the case of asymmetric populations the non-parametric Kruskal-Wallis test performs better than the parametric equivalent...