• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.379-385
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• 2010

This paper considers Bayesian approach to modeling a flexible regression function under functional measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under functional measurement error model without semiparametric component.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1645-1651
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• 2016

A lot of data, particularly in the medical field, contain variables that have a measurement error such as blood pressure and body mass index. On the other hand, recently smoothing methods are often used to solve a complex scientific problem. In this paper, we study a Bayesian curve-fitting under functional measurement error model. Especially, we extend our previous model by incorporating covariates free of measurement error. In this paper, we consider penalized splines for non-linear pattern. We employ a hierarchical Bayesian framework based on Markov Chain Monte Carlo methodology for fitting the model and estimating parameters. For application we use the data from the fifth wave (2012) of the Korea National Health and Nutrition Examination Survey data, a national population-based data. To examine the convergence of MCMC sampling, potential scale reduction factors are used and we also confirm a model selection criteria to check the performance.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.749-754
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• 2015

This article presents Bayesian approach to regression splines with knots on a grid of equally spaced sample quantiles of the independent variables under functional measurement error model.We consider small area model by using penalized splines of non-linear pattern. Specifically, in a basis functions of the regression spline, we use radial basis functions. To fit the model and estimate parameters we suggest a hierarchical Bayesian framework using Markov Chain Monte Carlo methodology. Furthermore, we illustrate the method in an application data. We check the convergence by a potential scale reduction factor and we use the posterior predictive p-value and the mean logarithmic conditional predictive ordinate to compar models.

• Journal of the Korean Statistical Society
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• v.13 no.2
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• pp.107-113
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• 1984

In a linear regression model the idependent variables are frequently subject to measurement errors. For this case, the problem of estimating unknown parameters has been extensively discussed in the literature while very few has been concerned with the effect of measurement errors on prediction. This paper investigates the behavior of the predicted values of the dependent variable in terms of the average mean square error of prediction (AMSEP). AMSEP may be used as a criterion for selecting an appropriate estimation method, for designing an estimation experiment, and for developing cost-effective future sampling schemes.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.152-160
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• 1993

In developing a quadratic regression relationship, independent variable is frequently measured with error. In this paper the integrated mean square error of prediction is developed for a quadratic functional relationship model as a measure of the effect of measurement error of the independent variable on the predicted values. The amount of the effect of error is presented and illustrated with an example.

• Korean Journal of Applied Biomechanics
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• v.21 no.4
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• pp.449-458
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• 2011

There are many functional methods for estimating the mean axis of rotation of a joint. However, it is still a controversial issue which method is superior. The purpose of this study was to compare functional methods for estimated axes of rotation from synthetic data. The comparison was made in terms of suitabilities on describing humans in sports. For a more practical situation, the axis error as well as measurement and marker movement error were applied to generated data. Simulations having 1000 times of 80 rotational displacements were performed. The functional methods used in the study were two transformation methods, two fitting methods, and one more transformation method called M. The M method is a combination of S$\ddot{o}$derk & Wedin(1993) and Mardia & Jupp(2000). Another factor of the study was angular velocity with levels of .01, .025, .05, .5 and 1 rad/s. The method M resulted in unbiased, stable, and consistent axis of rotation vectors in all levels of angular velocity except .01 rad/s. Therefore, the method M had the highest validity and reliability of all the methods. The fitting methods were very sensitive in small angular velocities and stable only in the velocities of more than .5 rad/s. The most suitable method for analyzing human motion by using marker photogrammetry is M.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.94-100
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• 1995

Vector autoregressive process disturbed by measurement error is a vector autoregressive process with nonlineat parametric restrictions on the parameter. A Newton-Raphson procedure for estimating the parameter which take advantage of the information contained in the restrictions is proposed.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.63-75
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• 1985

This paper considers a statistical calibration problem in which the standard as wel as the nonstandard measurement is subject to error. Since the classicla approach cannot handle this situation properly, a functional relationship model with additional feature of prediction is proposed. For the analysis of the problem four different approaches-two estimation techniques (ordinary and grouping least squares) combined with two prediction methods (classical and inverse prediction)-are considered. By Monte Carlo simulation the perromance of each approach is assessed in term of the probability of concentration. The simulation results indicate that the ordinary least squares with inverse prediction is generally preferred in interpolation while the grouping least squares with classical prediction turns out to be better in extrapolation.

• Journal of Sensor Science and Technology
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• v.11 no.3
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• pp.125-131
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• 2002

Respiratory air flow rate is necessarily measured for the pulmonary function evaluation. The currently used devices are exposed to the problems of measurement reliability and cross-patient infection. The present study introduced a new technique which converted the bidirectional air flow rate into averaged dynamic pressure based on the famous Bernoulli's energy conservation principle. Single use plastic sensing element was assembled within the flow tube(mouth piece) made of paper, which was named "functional single use flow tube". Experiment demonstrated only ${\pm}1.5%$ relative error in the standard 3L volume measurement procedure well within the error limit suggested by the American Thoracic Society(ATS). Disposable use design completely eliminated cross-patient infection. The present device is best useful and safe for clinical respiratory air flow measurement such as spirometry.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.28 no.1
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• pp.39-51
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• 2022

Background: The purpose of this study is to investigate the effect of neck and shoulder self-stretching exercise using audiovisual media on neck pain, postural alignment, and joint position error in women with chronic neck pain. Methods: The subjects included 20 women that gave consent to participate in the study voluntarily. They performed the self-stretching exercises using audiovisual media was carried out 20 minutes 5 times a week during 3 weeks. Neck disability index (NDI) and visual analogue scale (VAS) were used to measure the functional disability and pain, A pressure pain threshold was measured using an algometer, and a cervical range of motion (CROM) measurement tool was used to measure the range of motion and error of proprioceptive position sense of the cervical spine. To assess posture alignment, forward head angle (FHA), forward shoulder angle (FSA) were measured using image J software. Results: The neck pain intensity was statistically significantly within group (p<.05). Neck and shoulder functional disability were a statistically significant difference within group (p<.05). Splenius capitis and upper trapezius pressure pain threshold were statistically significant difference in within group (p<.05). The postural alignment was statistically significantly within group (p<.05). The cervical range of motion in neck extension, right and left lateral flexion were statistically significantly within group (p<.05). The joint position error in neck flexion, extension, right and left lateral flexion decreased statistically significantly within group (p<.05). Conclusion: Self-stretching exercise using audiovisual media increased the mobility of the neck, decreased neck pain and joint position error, and improved posture alignment. As a result, there was a positive effect by applying the self-stretching exercise using audiovisual media to people with neck pain. Based on this, it is thought that it can be used as the basis for research related to home training programs for healthy self-management.