• Korean Journal of Child Studies
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• v.17 no.1
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• pp.245-258
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• 1996

The purpose of this study was to examine the relationship between mother's parenting stress and child's temperament, mother's temperament, and poorness-of-fit. The subjects were 236 mothers of 4- to 6-year-old children in Seoul. Data was analyzed by correlation, analysis of variance, and stepwise regression analysis. Results showed that most poorness-of-fit of emotionality was due child's high-mother's high (CH-MH) and high-low (CH-ML) combination. Most poorness-of-fit (activity as well as sociability) was associated with child's low-mother's low (CL-ML) and low-high (CL-MH) combination. Mothers who had a highly emotional child and who were in poorness-of-fit emotionality perceived more hassles and more intensive daily parenting stress. It was also found that the most significant variable predicting mother's hassles and daily stress intensity was poorness-of-fit of emotionality, followed by mother's emotionality.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2721-2731
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• 2018

This study purposes to derive the predictive model for the cold tolerance of Brassica napus, using the data collected in the Tree Breeding Lab of Gyeongsang National University during July and August of 2016. Three Brassica napus samples were treated at each of low temperatures from $4^{\circ}C$ to $-12^{\circ}C$ by decrement of $4^{\circ}C$, step by step, and electrolyte leakage levels were measured at each stage. Electrolyte leakages were observed tangibly from $-4^{\circ}C$. We tried to fit the six nonlinear regression models to the electrolyte leakage data of Brassica napus: 3-parameter logistic model, baseline logistic model, 4-parameter logistic model, (4-1)-parameter logistic model, 3-parameter Gompertz model, and (3-1)-parameter Gompertz model. The baseline levels of the electrolyte leakage estimated by these models were 4.81%, 4.07%, 4.19%, 4.07%, 4.55%, and 0%, respectively. The estimated median lethal temperature, LT50, were $-5.87^{\circ}C$, $-6.31^{\circ}C$, $-6.05^{\circ}C$, $-6.35^{\circ}C$, $-4.98^{\circ}C$, and $-5.15^{\circ}C$, respectively. We compared and discussed the measures of goodness of fit to select the appropriate nonlinear regression model.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.375-382
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• 1999

Linear-by-linear association models are commonly used to analyze ordered categorical data. To fit these models appropriate scores need to be chosen. In this paper we perform sensitivity analyses in two-way contingency tables to investigate the effect of scores on goodness-of-fits and on tests of significance. In addition we show that the best score which yields the best fit of data can be selected based on the sensitivity analysis results.

• Environmental and Resource Economics Review
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• v.13 no.4
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• pp.717-734
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• 2004

This paper examined the statistical goodness-of-fit tests for biological growth model in bioeconomic analysis. Some authors estimated usually growth function for fish in the world. However, few studies have estimated growth equations for the bivalve species. Thus, this paper studied the common functional forms of fitting growth equations for cham scallops considering environmental factors and production styles. The following functional forms are considered: linear, log-reciprocal, double log, polynomial and linear with interactions. Results of fitting these various functional forms with real data are compared and evaluated using standard statistical goodness-of-fit tests. Results also indicate that log-reciprocal function is statistically the best fit to the real data. Therefore, the log-reciprocal function is decided the best function describing cham scallop biological growth and hence might be useful for economic evaluation(i.e., optimal harvesting time).

• Earthquakes and Structures
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• v.5 no.4
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• pp.439-459
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• 2013

Main objective of the present study is to determine the statistical properties and suitable probability distribution functions of spectral displacements from nonlinear static and nonlinear dynamic analysis within the frame work of Monte Carlo simulation for typical low rise and high rise RC framed buildings located in zone III and zone V and designed as per Indian seismic codes. Probabilistic analysis of spectral displacement is useful for strength assessment and loss estimation. To the author's knowledge, no study is reported in literature on comparison of spectral displacement including the uncertainties in capacity and demand in Indian context. In the present study, uncertainties in capacity of the building is modeled by choosing cross sectional dimensions of beams and columns, density and compressive strength of concrete, yield strength and elastic modulus of steel and, live load as random variables. Uncertainty in demand is modeled by choosing peak ground acceleration (PGA) as a random variable. Nonlinear static analysis (NSA) and nonlinear dynamic analysis (NDA) are carried out for typical low rise and high rise reinforced concrete framed buildings using IDARC 2D computer program with the random sample input parameters. Statistical properties are obtained for spectral displacements corresponding to performance point from NSA and maximum absolute roof displacement from NDA and suitable probability distribution functions viz., normal, Weibull, lognormal are examined for goodness-of-fit. From the hypothesis test for goodness-of-fit, lognormal function is found to be suitable to represent the statistical variation of spectral displacement obtained from NSA and NDA.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.263-271
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• 2013

This study presents a fuzzy varying coefficient regression model after deleting the outliers to improve the feasibility and effectiveness of the fuzzy regression model. The objective of our methodology is to allow the fuzzy regression coefficients to vary with a covariate, and simultaneously avoid the impact of data contaminated by outliers. In this paper, fuzzy regression coefficients are represented by Gaussian fuzzy numbers. We also formulate suitable goodness of fit to evaluate the performance of the proposed methodology. An example is given to demonstrate the effectiveness of our methodology.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.903-914
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• 2014

The inverse Weibull distribution has been proposed as a model in the analysis of life testing data. Also, inverse Weibull distribution has been recently derived as a suitable model to describe degradation phenomena of mechanical components such as the dynamic components (pistons, crankshaft, etc.) of diesel engines. In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the shape parameter in the inverse Weibull distribution under multiply type-II censoring. We also develop four modified empirical distribution function (EDF) type tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.1
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• pp.255-262
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• 2002

This paper presents a statistical analysis of empirical fragility curves for bridge. The empirical fragility curves are developed utilizing bridge damage data obtained from the 1995 Hyogoken Nanbu(Kobe) earthquake. Two-parameter lognormal distribution functions are used to represent the fragility curves with the parameters estimated by the maximum likelihood method. This paper also presents methods of testing the goodness of fit of the fragility curves and estimating the confidence intervals of the two parameters(median and log-standard deviation) of the distribution. An analytical interpretation of randomness and uncertainty associated with the median is provided.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2813-2827
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• 2018

Progressive censoring schemes have become quite popular in reliability study. Under progressive censored data, however, some units can be failed between two points of observation with exact times of failure of these units unobserved. For example, loss may arise in life-testing experiments when the failure times of some units were not observed due to mechanical or experimental difficulties. Therefore, multiply progressive censoring scheme was introduced. So, we derives a maximum likelihood estimator of the parameter of exponential distribution. And we introduced the goodness-of-fit test statistics using order statistic and Lorenz curve. We carried out Monte Carlo simulation to compare the proposed test statistics. In addition, real data set have been analysed. In Weibull and chi-squared distributions, the test statistics using Lorenz curve are more powerful than test statistics using order statistics.

• Journal of Korea Water Resources Association
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• v.43 no.9
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• pp.813-822
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• 2010

An important problem in frequency analysis is the estimation of the quantile for a certain return period. In frequency analysis an assumed probability distribution is fitted to the observed sample data to estimate the quantile at the upper tail corresponding to return periods which are usually much larger than the record length. In most cases, the selection of an appropriate probability distribution is based on goodness of fit tests. The goodness of fit test method can be described as a method for examining how well sample data agrees with an assumed probability distribution as its population. However it gives generally equal weight to differences between empirical and theoretical distribution functions corresponding to all the observations. In this study, the modified Anderson-Darling (AD) test statistics are provided using simulation and the power study are performed to compare the efficiency of other goodness of fit tests. The power test results indicate that the modified AD test has better rejection performances than the traditional tests. In addition, the applications to real world data are discussed and shows that the modified AD test may be a powerful test for selecting an appropriate distribution for frequency analysis when extreme cases are considered.