• Title/Summary/Keyword: Kolmogorov models

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A comparative study of established z score models for coronary artery diameters in 181 healthy Korean children

  • Ryu, Kyungguk;Yu, Jeong Jin;Jun, Hyun Ok;Shin, Eun Jung;Heo, Young Hee;Baek, Jae Suk;Kim, Young-Hwue;Ko, Jae-Kon
    • Clinical and Experimental Pediatrics
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    • v.60 no.11
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    • pp.373-378
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    • 2017
  • Purpose: The aim of this study was to investigate the statistical properties of four previously developed pediatric coronary artery z score models in healthy Korean children. Methods: The study subjects were 181 healthy Korean children, whose age ranged from 1 month to 15 years. The diameter of each coronary artery was measured using 2-dimensional echocardiography and converted to the z score in the four models (McCrindle, Olivieri, Dallaire, and Japanese model). Descriptive statistical analyses and 1-sample t tests were performed. Results: All calculated z scores had P values of ${\geq}0.050$ using the Kolmogorov-Smirnov test. The one sample t test showed that the mean z scores did not converge to zero except in 1 model, and the mean right coronary artery (RCA) z score was less than zero in all 4 models. The smaller RCA diameter in this study could be associated with the more distal measuring point used to avoid the conal branch. The percentage of subjects with extreme z score values (${\geq}2.0$ and ${\geq}2.5$) for the left main coronary artery (LMCA) seems to be higher in the Dallaire (4.9% and 3.3%) and Japanese models (7.1% and 3.8%). Conclusion: All 4 models showed statistical feasibility of normal distribution. More precise instructions would be needed for the measurement of the RCA. The higher percentage of extreme z scores for the LMCA is compatible with the basic understanding of anatomic variation in the LMCA.

Criterion of Test Statistics for Validation in Credit Rating Model (신용평가모형에서 타당성검증 통계량들의 판단기준)

  • Park, Yong-Seok;Hong, Chong-Sun;Lim, Han-Seung
    • Communications for Statistical Applications and Methods
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    • v.16 no.2
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    • pp.239-347
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    • 2009
  • This paper presents Kolmogorov-Smirnov, mean difference, AUROC and AR, four well known statistics that have been widely used for evaluating the discriminatory power of credit rating models. Criteria for these statistics are determined by the value of mean difference under the assumption of normality and equal standard deviation. Alternative criteria are proposed through the simulations according to various sample sizes, type II error rates, and the ratio of bads, also we suggest the meaning of statistic on the basis of discriminatory power. Finally we make a comparative study of the currently used guidelines and simulated results.

Importance of the Temporal Variability of Rainfall Statistics in Stochastic Rainfall Modeling (추계강우모형에서의 강우통계의 시간적 변동성 연구)

  • Kim, Dong-Kyun;Lee, Jin-Woo;Cho, Yong-Sik
    • 한국방재학회:학술대회논문집
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    • 2010.02a
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    • pp.51.2-51.2
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    • 2010
  • A novel approach of Poisson cluster stochastic rainfall generator was validated in its ability to reproduce important rainfall and watershed response characteristics at 104 locations of the United States. The suggested novel approach - The Hybrid Model(THM), as compared to the traditional ones, has an additional function to account for the year-to-year variability of rainfall statistics. The two-sample Kolmogorov-Smirnov test was used to see how well THM and traditional approach of Poisson cluster rainfall model reproduce the distribution of the following hydrologic variables: monthly maximum rainfall depths with 1, 3, 6, 12, and 24 hour duration, monthly maximum flow peaks at the virtual watersheds with Curve Number of 50, 60, 70, 80 and 90; and monthly runoff depths at the same virtual watersheds. In all of the testing variables, THM significantly outperformed the traditional approach. This result indicates that the year-to-year variability of rainfall statistics contains important information about the characteristics of rainfall processes that were not considered by the conventional approach of Poisson cluster rainfall modeling and that further considering it in rainfall simulation will enhance the performance of the rainfall models.

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Accuracy of 14 intraoral scanners for the All-on-4 treatment concept: a comparative in vitro study

  • Gozde, Kaya;Caglar, Bilmenoglu
    • The Journal of Advanced Prosthodontics
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    • v.14 no.6
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    • pp.388-398
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    • 2022
  • PURPOSE. This in vitro study aimed to evaluate the accuracy of 14 different intraoral scanners for the All-on-4 treatment concept. MATERIALS AND METHODS. Four implants were placed in regions 13, 16, 23, and 26 of an edentulous maxillary model that was poured with scannable Type 4 gypsum to imitate the All-on-4 concept. The cast was scanned 10 times for each of 14 intraoral scanners (Primescan, iTero 2, iTero 5D, Virtuo Vivo, Trios 3, Trios 4, CS3600, CS3700, Emerald, Emerald S, Medit i500, BenQ BIS-I, Heron IOS, and Aadva IOS 100P) after the polyether ether ketone scanbody was placed. For the control group, the gypsum model was scanned 10 times with an industrial scanner. The first of the 10 virtual models obtained from the industrial model was chosen as the reference model. For trueness, the data of the 14 dental scanners were superimposed with the reference model; for precision, the data of all 14 scanners were superimposed within the groups. Statistical analyses were performed using the Kolmogorov-Smirnov, Shapiro-Wilks, and Dunn's tests. RESULTS. Primescan showed the highest trueness and precision values (P < .005), followed by the iTero 5D scanner (P < .005). CONCLUSION. Some of these digital scanners can be used to make impressions within the All-on-4 concept. However, the possibility of data loss due to artifacts, reflections, and the inability to combine the data should be considered.

Statistical models from weigh-in-motion data

  • Chan, Tommy H.T.;Miao, T.J.;Ashebo, Demeke B.
    • Structural Engineering and Mechanics
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    • v.20 no.1
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    • pp.85-110
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    • 2005
  • This paper aims at formulating various statistical models for the study of a ten year Weigh-in-Motion (WIM) data collected from various WIM stations in Hong Kong. In order to study the bridge live load model it is important to determine the mathematical distributions of different load affecting parameters such as gross vehicle weights, axle weights, axle spacings, average daily number of trucks etc. Each of the above parameters is analyzed by various stochastic processes in order to obtain the mathematical distributions and the Maximum Likelihood Estimation (MLE) method is adopted to calculate the statistical parameters, expected values and standard deviations from the given samples of data. The Kolmogorov-Smirnov (K-S) method of approach is used to check the suitability of the statistical model selected for the particular parameter and the Monte Carlo method is used to simulate the distributions of maximum value stochastic processes of a series of given stochastic processes. Using the statistical analysis approach the maximum value of gross vehicle weight and axle weight in bridge design life has been determined and the distribution functions of these parameters are obtained under both free-flowing traffic and dense traffic status. The maximum value of bending moments and shears for wide range of simple spans are obtained by extrapolation. It has been observed that the obtained maximum values of the gross vehicle weight and axle weight from this study are very close to their legal limitations of Hong Kong which are 42 tonnes for gross weight and 10 tonnes for axle weight.

A copula based bias correction method of climate data

  • Gyamfi Kwame Adutwum;Eun-Sung Chung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.160-160
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    • 2023
  • Generally, Global Climate Models (GCM) cannot be used directly due to their inherent error arising from over or under-estimation of climate variables compared to the observed data. Several bias correction methods have been devised to solve this problem. Most of the traditional bias correction methods are one dimensional as they bias correct the climate variables separately. One such method is the Quantile Mapping method which builds a transfer function based on the statistical differences between the GCM and observed variables. Laux et al. introduced a copula-based method that bias corrects simulated climate data by employing not one but two different climate variables simultaneously and essentially extends the traditional one dimensional method into two dimensions. but it has some limitations. This study uses objective functions to address specifically, the limitations of Laux's methods on the Quantile Mapping method. The objective functions used were the observed rank correlation function, the observed moment function and the observed likelihood function. To illustrate the performance of this method, it is applied to ten GCMs for 20 stations in South Korea. The marginal distributions used were the Weibull, Gamma, Lognormal, Logistic and the Gumbel distributions. The tested copula family include most Archimedean copula families. Five performance metrics are used to evaluate the efficiency of this method, the Mean Square Error, Root Mean Square Error, Kolmogorov-Smirnov test, Percent Bias, Nash-Sutcliffe Efficiency and the Kullback Leibler Divergence. The results showed a significant improvement of Laux's method especially when maximizing the observed rank correlation function and when maximizing a combination of the observed rank correlation and observed moments functions for all GCMs in the validation period.

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Weibull Diameter Distribution Yield Prediction System for Loblolly Pine Plantations (테다소나무 조림지(造林地)에 대한 Weibull 직경분포(直經分布) 수확예측(收穫豫測) 시스템에 관(關)한 연구(硏究))

  • Lee, Young-Jin;Hong, Sung-Cheon
    • Journal of Korean Society of Forest Science
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    • v.90 no.2
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    • pp.176-183
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    • 2001
  • Loblolly pine (Pinus taeda L.) is the most economically important timber producing species in the southern United States. Much attention has been given to predicting diameter distributions for the solution of multiple-product yield estimates. The three-parameter Weibull diameter distribution yield prediction systems were developed for loblolly pine plantations. A parameter recovery procedure for the Weibull distribution function based on four percentile equations was applied to develop diameter distribution yield prediction models. Four percentiles (0th, 25th, 50th, 95th) of the cumulative diameter distribution were predicted as a function of quadratic mean diameter. Individual tree height prediction equations were developed for the calculation of yields by diameter class. By using individual tree content prediction equations, expected yield by diameter class can be computed. To reduce rounding-off errors, the Weibull cumulative upper bound limit difference procedure applied in this study shows slightly better results compared with upper and lower bound procedure applied in the past studies. To evaluate this system, the predicted diameter distributions were tested against the observed diameter distributions using the Kolmogorov-Smirnov two sample test at the ${\alpha}$=0.05 level to check if any significant differences existed. Statistically, no significant differences were detected based on the data from 516 evaluation data sets. This diameter distribution yield prediction system will be useful in loblolly pine stand structure modeling, in updating forest inventories, and in evaluating investment opportunities.

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On the Small Sample Distribution and its Consistency with the Large Sample Distribution of the Chi-Squared Test Statistic for a Two-Way Contigency Table with Fixed Margins (주변값이 주어진 이원분할표에 대한 카이제곱 검정통계량의 소표본 분포 및 대표본 분포와의 일치성 연구)

  • Park, Cheol-Yong;Choi, Jae-Sung;Kim, Yong-Gon
    • Journal of the Korean Data and Information Science Society
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    • v.11 no.1
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    • pp.83-90
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    • 2000
  • The chi-squared test statistic is usually employed for testing independence of two categorical variables in a two-way contingency table. It is well known that, under independence, the test statistic has an asymptotic chi-squared distribution under multinomial or product-multinomial models. For the case where both margins fixed, the sampling model of the contingency table is a multiple hypergeometric distribution and the chi-squared test statistic follows the same limiting distribution. In this paper, we study the difference between the small sample and large sample distributions of the chi-squared test statistic for the case with fixed margins. For a few small sample cases, the exact small sample distribution of the test statistic is directly computed. For a few large sample sizes, the small sample distribution of the statistic is generated via a Monte Carlo algorithm, and then is compared with the large sample distribution via chi-squared probability plots and Kolmogorov-Smirnov tests.

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Does Breast Cancer Drive the Building of Survival Probability Models among States? An Assessment of Goodness of Fit for Patient Data from SEER Registries

  • Khan, Hafiz;Saxena, Anshul;Perisetti, Abhilash;Rafiq, Aamrin;Gabbidon, Kemesha;Mende, Sarah;Lyuksyutova, Maria;Quesada, Kandi;Blakely, Summre;Torres, Tiffany;Afesse, Mahlet
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.12
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    • pp.5287-5294
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    • 2016
  • Background: Breast cancer is a worldwide public health concern and is the most prevalent type of cancer in women in the United States. This study concerned the best fit of statistical probability models on the basis of survival times for nine state cancer registries: California, Connecticut, Georgia, Hawaii, Iowa, Michigan, New Mexico, Utah, and Washington. Materials and Methods: A probability random sampling method was applied to select and extract records of 2,000 breast cancer patients from the Surveillance Epidemiology and End Results (SEER) database for each of the nine state cancer registries used in this study. EasyFit software was utilized to identify the best probability models by using goodness of fit tests, and to estimate parameters for various statistical probability distributions that fit survival data. Results: Statistical analysis for the summary of statistics is reported for each of the states for the years 1973 to 2012. Kolmogorov-Smirnov, Anderson-Darling, and Chi-squared goodness of fit test values were used for survival data, the highest values of goodness of fit statistics being considered indicative of the best fit survival model for each state. Conclusions: It was found that California, Connecticut, Georgia, Iowa, New Mexico, and Washington followed the Burr probability distribution, while the Dagum probability distribution gave the best fit for Michigan and Utah, and Hawaii followed the Gamma probability distribution. These findings highlight differences between states through selected sociodemographic variables and also demonstrate probability modeling differences in breast cancer survival times. The results of this study can be used to guide healthcare providers and researchers for further investigations into social and environmental factors in order to reduce the occurrence of and mortality due to breast cancer.

Infinite Failure NHPP Software Mixture Reliability Growth Model Base on Record Value Statistics (기록값 통계량에 기초한 무한고장 NHPP 소프트웨어 혼합 신뢰성장 모형에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul;Kim, Kyung-Soo
    • Convergence Security Journal
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    • v.7 no.3
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    • pp.51-60
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    • 2007
  • Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, exponential distribution and Rayleigh distribution model was reviewed, proposes the mixture reliability model, which made out efficiency substituted for situation for failure time Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using S27 data set for the sake of proposing shape parameter of the mixture distribution was employed. This analysis of failure data compared with the mixture distribution model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

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