• Title/Summary/Keyword: statistical estimator

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Temporal hierarchical forecasting with an application to traffic accident counts (시간적 계층을 이용한 교통사고 발생건수 예측)

  • Jun, Gwanyoung;Seong, Byeongchan
    • The Korean Journal of Applied Statistics
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    • v.31 no.2
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    • pp.229-239
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    • 2018
  • This paper introduces how to adopt the concept of temporal hierarchies to forecast time series data. Similarly as in hierarchical cross-sectional data, temporal hierarchies can be constructed for any time series data by means of non-overlapping temporal aggregation. Reconciliation forecasts with temporal hierarchies result in more accurate and robust forecasts when compared with the independent base and bottom-up forecasts. As an empirical example, we forecast traffic accident counts with temporal hierarchies and observe that reconciliation forecasts are superior to the base and bottom-up forecasts in terms of forecast accuracy.

The Study for NHPP Software Reliability Growth Model Based on Hyper-exponential Distribution (초지수분포(Hyper-exponential)를 이용한 소프트웨어 신뢰성장 모형에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.7 no.1
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    • pp.45-53
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    • 2007
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the hyper-exponential distribution reliability model, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method. For model determination and selection, explored goodness of fit (the error sum of squares). The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution (shape 0.1 & scale 1) of Minitab (version 14) statistical package.

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Comparative analysis of Bayesian and maximum likelihood estimators in change point problems with Poisson process

  • Kitabo, Cheru Atsmegiorgis;Kim, Jong Tae
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.1
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    • pp.261-269
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    • 2015
  • Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum like-lihood estimator and remains good choice specially in confidence interval statistical inference.

A Complex Sampling Design for the Estimation of Korean Livestock Production Cost (축산물생산비조사를 위한 복합표본설계)

  • Kim, Soo-Taek;Kim, Young-Won
    • The Korean Journal of Applied Statistics
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    • v.21 no.4
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    • pp.675-694
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    • 2008
  • We propose a new sampling design for the Korean Livestock Production Cost Survey. In this sampling design, the survey population is derived from the 2005’s agricultural census of Korea. And coefficient of variation(CV) is estimated from the current livestock production cost survey data, and the estimated CV’s are used to find the optimal sample size which satisfies the predetermined precision of estimation. In order to save the enumeration cost, the agriculture enumeration districts are used as a primary sampling unit(psu). Final sample is selected by double sampling. Also, we propose the estimator which is able to reflect the change of the population of livestock production households.

A Study on 7th Probability and Statistics Education In Mathematics 1 Textbooks in Korea (수학 I 검정교과서 확률통계 영역에 대한 연구)

  • Lee Sang Bock;Sohn Joong-Kweon;Chung Sung Suck
    • The Korean Journal of Applied Statistics
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    • v.18 no.1
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    • pp.197-210
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    • 2005
  • In Korea, mathematics education has been taken according to the 7th national mathematics curriculum renovated by the Ministry of Education and Human Resources Development announcement in 1997. The education of probability and Statistics has been carried out as a part of this curriculum. We analyze and compare mathematics 1 textbooks for 11-12 grade students. Descriptions of random variable, sample variance and sample standard deviation, distribution of sample mean, and etc. which are on some textbooks, are misleaded in school education. We suggest the unbiased estimator of sample variance in accordance with textbooks and central limit theorem of sample mean under normal population.

On the Use of Adaptive Weights for the F-Norm Support Vector Machine

  • Bang, Sung-Wan;Jhun, Myoung-Shic
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.829-835
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    • 2012
  • When the input features are generated by factors in a classification problem, it is more meaningful to identify important factors, rather than individual features. The $F_{\infty}$-norm support vector machine(SVM) has been developed to perform automatic factor selection in classification. However, the $F_{\infty}$-norm SVM may suffer from estimation inefficiency and model selection inconsistency because it applies the same amount of shrinkage to each factor without assessing its relative importance. To overcome such a limitation, we propose the adaptive $F_{\infty}$-norm ($AF_{\infty}$-norm) SVM, which penalizes the empirical hinge loss by the sum of the adaptively weighted factor-wise $L_{\infty}$-norm penalty. The $AF_{\infty}$-norm SVM computes the weights by the 2-norm SVM estimator and can be formulated as a linear programming(LP) problem which is similar to the one of the $F_{\infty}$-norm SVM. The simulation studies show that the proposed $AF_{\infty}$-norm SVM improves upon the $F_{\infty}$-norm SVM in terms of classification accuracy and factor selection performance.

Comparison of semiparametric methods to estimate VaR and ES (조건부 Value-at-Risk와 Expected Shortfall 추정을 위한 준모수적 방법들의 비교 연구)

  • Kim, Minjo;Lee, Sangyeol
    • The Korean Journal of Applied Statistics
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    • v.29 no.1
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    • pp.171-180
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    • 2016
  • Basel committee suggests using Value-at-Risk (VaR) and expected shortfall (ES) as a measurement for market risk. Various estimation methods of VaR and ES have been studied in the literature. This paper compares semi-parametric methods, such as conditional autoregressive value at risk (CAViaR) and conditional autoregressive expectile (CARE) methods, and a Gaussian quasi-maximum likelihood estimator (QMLE)-based method through back-testing methods. We use unconditional coverage (UC) and conditional coverage (CC) tests for VaR, and a bootstrap test for ES to check the adequacy. A real data analysis is conducted for S&P 500 index and Hyundai Motor Co. stock price index data sets.

Modeling Clustered Interval-Censored Failure Time Data with Informative Cluster Size (군집의 크기가 생존시간에 영향을 미치는 군집 구간중도절단된 자료에 대한 준모수적 모형)

  • Kim, Jinheum;Kim, Youn Nam
    • The Korean Journal of Applied Statistics
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    • v.27 no.2
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    • pp.331-343
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    • 2014
  • We propose two estimating procedures to analyze clustered interval-censored data with an informative cluster size based on a marginal model and investigate their asymptotic properties. One is an extension of Cong et al. (2007) to interval-censored data and the other uses the within-cluster resampling method proposed by Hoffman et al. (2001). Simulation results imply that the proposed estimators have a better performance in terms of bias and coverage rate of true value than an estimator with no adjustment of informative cluster size when the cluster size is related with survival time. Finally, they are applied to lymphatic filariasis data adopted from Williamson et al. (2008).

Improved GLR Method to Instrument Failure Detection (측정기기 고장진단에 관한 개선된 GLR방식)

  • Hak Yeoung Jeong;Soon Heung Chang
    • Nuclear Engineering and Technology
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    • v.17 no.2
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    • pp.83-97
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    • 1985
  • The Generalized Likelihood Ratio (GLR) method performs statistical tests on the innovations sequence of a Kalman-Buchy filter state estimator for system failure detection and its identification. However, the major drawback of the conventional GLR is to hypothesize particular failure type in each case. In this paper, a method to solve this drawback is proposed. The improved GLR method is applied to a PWR pressurizer and gives successful results in detection and identification of any failure. Furthermore, some benefit on the processing time lier each cycle of failure detection and its identification can be accompanied.

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Parallelism Test of Slope in a Several Simple Linear Regression Model based on a Sequential Slope (여러개의 단순 선형 회귀모형에서 순차기울기를 이용한 평행성 검정)

  • Kim, Juhie;Kim, Dongjae
    • The Korean Journal of Applied Statistics
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    • v.26 no.6
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    • pp.1009-1018
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    • 2013
  • Regression analysis is useful to understand the relationship of variables; however, we need to test if the slope of each regression lines is the same when comparing several populations. This paper suggests a new parallelism test for several linear regression lines. We use F-test of ANOVA and Kruskal-Wallis (1952) tests after obtaining slope estimator from a sequential slope. In addition, a Monte Carlo simulation study is adapted to compare the power of the proposed methods with those of Park and Kim (2009).