• Genomics & Informatics
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• v.19 no.4
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• pp.36.1-36.11
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• 2021

Predicting individual traits and diseases from genetic variants is critical to fulfilling the promise of personalized medicine. The genetic variants from genome-wide association studies (GWAS), including variants well below GWAS significance, can be aggregated into highly significant predictions across a wide range of complex traits and diseases. The recent arrival of large-sample public biobanks enables highly accurate polygenic predictions based on genetic variants across the whole genome. Various statistical methodologies and diverse computational tools have been introduced and developed to computed the polygenic risk score (PRS) more accurately. However, many researchers utilize PRS tools without a thorough understanding of the underlying model and how to specify the parameters for the best performance. It is advantageous to study the statistical models implemented in computational tools for PRS estimation and the formulas of parameters to be specified. Here, we review a variety of recent statistical methodologies and computational tools for PRS computation.

• Journal of Environmental Impact Assessment
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• v.29 no.4
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• pp.272-285
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• 2020

We investigated statistical evaluation parameters for 3D meteorological and air quality models and selected several quantitative indicator references, and summarized the reference values of the statistical parameters for domestic air quality modeling researcher. The finally selected 9 statistical parameters are MB (Mean Bias), ME (Mean Error), MNB (Mean Normalized Bias Error), MNE (Mean Absolute Gross Error), RMSE (Root Mean Square Error), IOA (Index of Agreement), R (Correlation Coefficient), FE (Fractional Error), FB (Fractional Bias), and the associated reference values are summarized. The results showed that MB and ME have been widely used in evaluating the meteorological model output, and NMB and NME are most frequently used for air quality model results. In addition, discussed are the presentation diagrams such as Soccer Plot, Taylor diagram, and Q-Q (Quantile-Quantile) diagram. The current results from our study is expected to be effectively used as the statistical evaluation parameters suitable for situation in Korea considering various characteristics such as including the mountainous surface areas.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.519-531
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• 2017

We consider goodness-of-fit test statistics for Weibull distributions when data are randomly censored and the parameters are unknown. Koziol and Green (Biometrika, 63, 465-474, 1976) proposed the $Cram\acute{e}r$-von Mises statistic's randomly censored version for a simple hypothesis based on the Kaplan-Meier product limit of the distribution function. We apply their idea to the other statistics based on the empirical distribution function such as the Kolmogorov-Smirnov and Liao and Shimokawa (Journal of Statistical Computation and Simulation, 64, 23-48, 1999) statistics. The latter is a hybrid of the Kolmogorov-Smirnov, $Cram\acute{e}r$-von Mises, and Anderson-Darling statistics. These statistics as well as the Koziol-Green statistic are considered as test statistics for randomly censored Weibull distributions with estimated parameters. The null distributions depend on the estimation method since the test statistics are not distribution free when the parameters are estimated. Maximum likelihood estimation and the graphical plotting method with the least squares are considered for parameter estimation. A simulation study enables the Liao-Shimokawa statistic to show a relatively high power in many alternatives; however, the null distribution heavily depends on the parameter estimation. Meanwhile, the Koziol-Green statistic provides moderate power and the null distribution does not significantly change upon the parameter estimation.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1927-1929
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• 2000

PD indicates the inception and progress of degradation of solid insulation system, so it has been used to determine degradation of insulation. PD provides means for detection and recognition of defects. However, there is still marked difficult to recognize defects by PD methods. In this paper, we investigated properties of PD in solid insulation by using statistical method with surface discharge, electrical tree and void discharge with source of discharge, we used statistical parameters of PD distributions specified such as $H_n(q)$, $H_{an}(\phi)$, $H_n(\phi)$, $H_a(\phi)$. The parameters induced from its specified distributions are average discharge, average repetition rate, Skewness, Kurtosis, asymmetry and correlation. From the parameters, we classified PD patterns and built up DB(data-base).

• Journal of radiological science and technology
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• v.45 no.5
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• pp.439-448
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• 2022

The purpose of this study was to analyze the results from statistical process control (SPC) to recommend upper and lower control limits for planning parameters based on delivery quality assurance (DQA) results and establish our institutional guidelines regarding planning parameters for helical tomotherapy (HT). A total of 53 brain, 41 head and neck (H & N), and 51 pelvis cases who had passing or failing DQA measurements were selected. The absolute point dose difference (DD) and the global gamma passing rate (GPR) for all patients were analyzed. Control charts were used to evaluate upper and lower control limits (UCL and LCL) for all assessed treatment planning parameters. Treatment planning parameters were analyzed to provide its range for DQA pass cases. We confirmed that the probability of DQA failure was higher when the proportion of leaf open time (LOT) below 100 ms was greater than 30%. LOT and gantry period (GP) were significant predictor for DQA failure using the SPC method. We investigated the availability of the SPC statistic method to establish the local planning guideline based on DQA results for HT system. The guideline of each planning parameter in HT may assist in the prediction of DQA failure using the SPC statistic method in the future.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.287-295
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• 1998

A random fuzzy linear regression model is introduced, which includes both randomness and fuzziness. Estimators for the parameters are suggested, which are derived mainly using properties of randomness.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.115-120
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• 2003

Inference for probability P(Y

• Journal of Electrical Engineering and information Science
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• v.3 no.3
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• pp.355-365
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• 1998

The purposes of this study are to propose a network for the characterizing of the input data and to show how to design predictive neural net재가 expert system which doesn't need previous knowledge base. We derived this network from the radial basis function networks(RBFN), and named it as a statistical EBFN. The proposed network can replace the statistical methods for analyzing dynamic relations between target disease and other parameters in medical studies. We compared statistical RBFN with the probabilistic neural network(PNN) and fuzzy logic(FL). And we testified our method in the diabetes prediction and compared our method with the well-known multilayer perceptron(MLP) neural network one, and showed good performance of our network. At last, we developed the diabetes prediction expert system based on the proposed statistical RBFN without previous knowledge base. Not only the applicability of the characterizing of parameters related to diabetes and construction of the diabetes prediction expert system but also wide applicabilities has the proposed statistical RBFN to other similar problems.

• The Journal of Churna Manual Medicine for Spine and Nerves
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• v.10 no.1
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• pp.47-61
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• 2015

Objectives : The purpose of this study is body parameters characteristics through posture analysis system of musculoskeletal problem patient Methods : Posture analysis system were performed for 164 patients to measure body parameters such as Q-angle, body inclination, neck inclination, PCMT(posterior cervical muscle tension), Knee flexion and posture balance. Statistical analysis using statistical analysis techniques and Pearson correlation coefficients was performed to assess the body parameters obtained by posture analysis system. Results : More than half of people out of 164 reported low back pain, 34.8% of the total was found to have neck pain. There was not a significant difference between genders from the characteristics of gender based body parameters expect for the statistical difference in Q angle, PCMT. There was a significant correlation between low back pain and multiple response status. There was a significant correlations between knee pain and Q angle. Also There was a significant correlations between pelvic pain and posture balance of ankle. Conclusions : Posture analysis system can be used to perform the analysis in place of X-ray measuring body posture and clinical parameters. The results of this study are expected to be the basis for further research on the clinical application of posture analysis system.

• Journal of the Korean Statistical Society
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• v.17 no.2
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• pp.61-80
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• 1988

For testing homogeneity of scale parameters aginst ordered alternatives, some nonparametric test statistics based on pairwise ranking method are proposed. The proposed tests are distribution-free. The asymptotic distributions of the proposed statistcs are also investigated. It is shown that the Pitman efficiencies of the proposed rank tests are the same as those of the corresponding two-sample rank tests in the scale problem. A small-sample Monte Carlo study is also performed. The results show that the proposed tests are robust and efficient.