• Title/Summary/Keyword: statistical correction

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Does Correction Factor Vary with Solar Cycle?

  • Chang, Heon-Young;Oh, Sung-Jin
    • Journal of Astronomy and Space Sciences
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    • v.29 no.2
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    • pp.97-101
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    • 2012
  • Monitoring sunspots consistently is the most basic step required to study various aspects of solar activity. To achieve this goal, the observers must regularly calculate their own correction factor $k$ and keep it stable. Relatively recently, two observing teams in South Korea have presented interesting papers which claim that revisions that take the yearly-basis $k$ into account lead to a better agreement with the international relative sunspot number $R_i$, and that yearly $k$ apparently varies with the solar cycle. In this paper, using artificial data sets we have modeled the sunspot numbers as a superposition of random noise and a slowly varying background function, and attempted to investigate whether the variation in the correction factor is coupled with the solar cycle. Regardless of the statistical distributions of the random noise, we have found the correction factor increases as sunspot numbers increase, as claimed in the reports mentioned above. The degree of dependence of correction factor $k$ on the sunspot number is subject to the signal-to-noise ratio. Therefore, we conclude that apparent dependence of the value of the correction factor $k$ on the phase of the solar cycle is not due to a physical property, but a statistical property of the data.

Unbiasedness or Statistical Efficiency: Comparison between One-stage Tobit of MLE and Two-step Tobit of OLS

  • Park, Sun-Young
    • International Journal of Human Ecology
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    • v.4 no.2
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    • pp.77-87
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    • 2003
  • This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

A Simple Bias-Correction Rule for the Apparent Prediction Error

  • Beong-Soo So
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.146-154
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    • 1995
  • By using simple Taylor expansion, we derive an easy bias-correction rule for the apparent prodiction error of the predictor defined by the general M-estimators with respect to an arbitrary measure of prediction error. Our method has a considerable computational advantage over the previous methods based on the resampling thchnique such as Cross-validaton and Boothtrap. Connections with AIC, Cross-Validation and Boothtrap are discussed too.

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An Algorithm for Baseline Correction of SELDI/MALDI Mass Spectrometry Data

  • Lee, Kyeong-Eun
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.4
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    • pp.1289-1297
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    • 2006
  • Before other statistical data analysis the preprocessing steps should be performed adequately to have meaningful results. These steps include processes such as baseline correction, normalization, denoising, and multiple alignment. In this paper an algorithm for baseline correction is proposed with using the piecewise cubic Hermite interpolation with block-selected points and local minima after denoising for SELDI or MALDI mass spectrometry data.

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An Empirical Study on the Wealth Effect

  • Kim, Yon Hyong;Chong, Young Suk
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.89-99
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    • 2003
  • The primary purpose of this paper is to estimate the wealth effect. We establish a linear relationships between household consumption, labor income, and stock price index. Each variable is nonstationary. And so, it contains a unit root. However, as the result of the test about cointegrating relations, the variables are cointegrated which implies the error term is stationary. The cointegrating parameter that the marginal propensity to consume out of stock price is 0.08%. The result of estimation shows the error correction is -0.62 and the significant level is also high. The error correction term indicates a rather rapid adjustment to deviations from the long run equilibrium relations.

Context-sensitive Spelling Error Correction using Eojeol N-gram (어절 N-gram을 이용한 문맥의존 철자오류 교정)

  • Kim, Minho;Kwon, Hyuk-Chul;Choi, Sungki
    • Journal of KIISE
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    • v.41 no.12
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    • pp.1081-1089
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    • 2014
  • Context-sensitive spelling-error correction methods are largely classified into rule-based methods and statistical data-based methods, the latter of which is often preferred in research. Statistical error correction methods consider context-sensitive spelling error problems as word-sense disambiguation problems. The method divides a vocabulary pair, for correction, which consists of a correction target vocabulary and a replacement candidate vocabulary, according to the context. The present paper proposes a method that integrates a word-phrase n-gram model into a conventional model in order to improve the performance of the probability model by using a correction vocabulary pair, which was a result of a previous study performed by this research team. The integrated model suggested in this paper includes a method used to interpolate the probability of a sentence calculated through each model and a method used to apply the models, when both methods are sequentially applied. Both aforementioned types of integrated models exhibit relatively high accuracy and reproducibility when compared to conventional models or to a model that uses only an n-gram.

Correction Method for Orientation of Cylindrical Moving Part in Micro-Positioning Device (정밀 위치 결정 기구에서 원통형 구동부의 자세 보정)

  • Jo, Nam-Gyu;Kim, Do-Hyeon;Gwon, Gi-Hwan
    • Journal of the Korean Society for Precision Engineering
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    • v.18 no.11
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    • pp.42-50
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    • 2001
  • In this paper, a new technique and theory are proposed which correct the orientation (inclination of a vertical axis) of a cylinder in vertical-micro positioning device. An algorithm for determining the orientation of the cylinder with a pair of displacement sensor units is derived and two types of the correction methods are described. To assess the performance and efficiency of the developed correction technique, the compensation errors originated from the correction algorithm and the machined characteristics of cylinder surface are evaluated from the geometrical considerations and the statistical techniques. Based upon the evaluation results, the maximum compensation error is estimated for the orientation of cylinder and the optimum correction technique is derived.

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A Comparison Study on Statistical Modeling Methods (통계모델링 방법의 비교 연구)

  • Noh, Yoojeong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.5
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    • pp.645-652
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    • 2016
  • The statistical modeling of input random variables is necessary in reliability analysis, reliability-based design optimization, and statistical validation and calibration of analysis models of mechanical systems. In statistical modeling methods, there are the Akaike Information Criterion (AIC), AIC correction (AICc), Bayesian Information Criterion, Maximum Likelihood Estimation (MLE), and Bayesian method. Those methods basically select the best fitted distribution among candidate models by calculating their likelihood function values from a given data set. The number of data or parameters in some methods are considered to identify the distribution types. On the other hand, the engineers in a real field have difficulties in selecting the statistical modeling method to obtain a statistical model of the experimental data because of a lack of knowledge of those methods. In this study, commonly used statistical modeling methods were compared using statistical simulation tests. Their advantages and disadvantages were then analyzed. In the simulation tests, various types of distribution were assumed as populations and the samples were generated randomly from them with different sample sizes. Real engineering data were used to verify each statistical modeling method.

The Eccentric Properties of the Chi-Squared Test with Yates' Continuity Correction in Extremely Unbalanced 2×2 Contingency Table

  • Kang, Seung-Ho;Kwon, Tae-Hyuk
    • The Korean Journal of Applied Statistics
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    • v.23 no.4
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    • pp.777-781
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    • 2010
  • Yates' continuity correction of the chi-squared test for testing the homogeneity of two binomial proportions in $2{\times}2$ contingency tables is developed to lower the value of the test statistic slightly. The effect of continuity correction is expected to decrease as the sample size increases. However, in extremely unbalanced $2{\times}2$ contingency tables, we find some cases where the effect of continuity correction is eccentric and is larger than expected. In such cases, we conclude that the chi-squared test with continuity correction should not be employed as a test statistic in both asymptotic tests and exact tests.

A Joint Statistical Model for Word Spacing and Spelling Error Correction Simultaneously (띄어쓰기 및 철자 오류 동시교정을 위한 통계적 모델)

  • Noh, Hyung-Jong;Cha, Jeong-Won;Lee, GaryGeun-Bae
    • Journal of KIISE:Software and Applications
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    • v.34 no.2
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    • pp.131-139
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    • 2007
  • In this paper, we present a preprocessor which corrects word spacing errors and spelling correction errors simultaneously. The proposed expands noisy-channel model so that it corrects both errors in colloquial style sentences effectively, while preprocessing algorithms have limitations because they correct each error separately. Using Eojeol transition pattern dictionary and statistical data such as n-gram and Jaso transition probabilities, it minimizes the usage of dictionaries and produces the corrected candidates effectively. In experiments we did not get satisfactory results at current stage, we noticed that the proposed methodology has the utility by analyzing the errors. So we expect that the preprocessor will function as an effective error corrector for general colloquial style sentence by doing more improvements.