• 제목/요약/키워드: generalized likelihood ratio test

검색결과 37건 처리시간 0.024초

TESTS FOR VARYING-COEFFICIENT PARTS ON VARYING-COEFFICIENT SINGLE-INDEX MODEL

  • Huang, Zhensheng;Zhang, Riquan
    • 대한수학회지
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    • 제47권2호
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    • pp.385-407
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    • 2010
  • To study the relationship between the levels of chemical pollutants and the number of daily total hospital admissions for respiratory diseases and to find the effect of temperature/relative humidity on the admission number, Wong et al. [17] introduced the varying-coefficient single-index model (VCSIM). As pointed out, it is a popular multivariate nonparametric fitting technique. However, the tests of the model have not been very well developed. In this paper, based on the estimators obtained by the local linear technique, the average method and the one-step back-fitting technique in the VCSIM, the generalized likelihood ratio (GLR) tests for varying-coefficient parts on the VCSIM are established. Under the null hypotheses the new proposed GLR tests follow the $\chi^2$-distribution asymptotically with scale constant and degree of freedom independent of the nuisance parameters, known as Wilks phenomenon. Simulations are conducted to evaluate the test procedure empirically. A real example is used to illustrate the performance of the testing approach.

일반공산비 기법을 이용한 SDINS/GPS 통합시스템의 고장 검출 및 격리 (Fault Detection and Isolation of Integrated SDINS/GPS System Using the Generalized Likelihood Ratio)

  • 신정훈;임유철;유준
    • 한국군사과학기술학회지
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    • 제3권2호
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    • pp.140-148
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    • 2000
  • This paper presents a fault detection and isolation(FDI) method based on Generalized Likelihood Ratio(GLR) test for the tightly coupled SDINS/CPS system. The GLR test is known to have the capability of detecting an assumed change while estimating its occurrence time and magnitude, and isolating the changing part. Once a fault is detected even if we don't know if the fault occurrs at either INS or GPS, multi-hypothesized GLR scheme performs the fault isolation between INS and GPS, and find which satellite malfunctions. However, in the INS faulty case, it turned out to fail to accomodate the fault isolation between accelerometer and gyroscope due to the coupling effects and a poor observability of the system. Hence, to isolate the INS fault, it needs to change the attitude of the vehicle resulting in enhancing the degree of observability.

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일반화된 샘플링 계획에서의 가설 검정 (A Hypothesis Test under the Generalized Sampling Plan)

  • 김명수;오근태
    • 품질경영학회지
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    • 제26권4호
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    • pp.79-87
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    • 1998
  • This paper considers the problem of testing a one-sided hypothesis under the generalized sampling plan which is defined by a sequence of independent Bernoulli trials. A certain lexicographic order is defined for the boundary points of the sampling plan. It is shown that the family of probability mass function defined on the boundary points has monotone likelihood ratio, and that the test function is uniformly most powerful.

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Mutual Information and Redundancy for Categorical Data

  • Hong, Chong-Sun;Kim, Beom-Jun
    • Communications for Statistical Applications and Methods
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    • 제13권2호
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    • pp.297-307
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    • 2006
  • Most methods for describing the relationship among random variables require specific probability distributions and some assumptions of random variables. The mutual information based on the entropy to measure the dependency among random variables does not need any specific assumptions. And the redundancy which is a analogous version of the mutual information was also proposed. In this paper, the redundancy and mutual information are explored to multi-dimensional categorical data. It is found that the redundancy for categorical data could be expressed as the function of the generalized likelihood ratio statistic under several kinds of independent log-linear models, so that the redundancy could also be used to analyze contingency tables. Whereas the generalized likelihood ratio statistic to test the goodness-of-fit of the log-linear models is sensitive to the sample size, the redundancy for categorical data does not depend on sample size but its cell probabilities itself.

Testing of Poisson Incidence Rate Restriction

  • Singh, Karan;Shanmugam, Ramalingam
    • International Journal of Reliability and Applications
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    • 제2권4호
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    • pp.263-268
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    • 2001
  • Shanmugam(1991) generalized the Poisson distribution to capture a restriction on the incidence rate $\theta$ (i.e. $\theta$$\beta$, an unknown upper limit), and named it incidence rate restricted Poisson (IRRP) distribution. Using Neyman's C($\alpha$) concept, Shanmugam then devised a hypothesis testing procedure for $\beta$ when $\theta$ remains unknown nuisance parameter. Shanmugam's C ($\alpha$) based .results involve inverse moments which are not easy tools, This article presents an alternate testing procedure based on likelihood ratio concept. It turns out that likelihood ratio test statistic offers more power than the C($\alpha$) test statistic. Numerical examples are included.

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Improved Parameter Estimation with Threshold Adaptation of Cognitive Local Sensors

  • Seol, Dae-Young;Lim, Hyoung-Jin;Song, Moon-Gun;Im, Gi-Hong
    • Journal of Communications and Networks
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    • 제14권5호
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    • pp.471-480
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    • 2012
  • Reliable detection of primary user activity increases the opportunity to access temporarily unused bands and prevents harmful interference to the primary system. By extracting a global decision from local sensing results, cooperative sensing achieves high reliability against multipath fading. For the effective combining of sensing results, which is generalized by a likelihood ratio test, the fusion center should learn some parameters, such as the probabilities of primary transmission, false alarm, and detection at the local sensors. During the training period in supervised learning, the on/off log of primary transmission serves as the output label of decision statistics from the local sensor. In this paper, we extend unsupervised learning techniques with an expectation maximization algorithm for cooperative spectrum sensing, which does not require an external primary transmission log. Local sensors report binary hard decisions to the fusion center and adjust their operating points to enhance learning performance. Increasing the number of sensors, the joint-expectation step makes a confident classification on the primary transmission as in the supervised learning. Thereby, the proposed scheme provides accurate parameter estimates and a fast convergence rate even in low signal-to-noise ratio regimes, where the primary signal is dominated by the noise at the local sensors.

The GARCH-GPD in market risks modeling: An empirical exposition on KOSPI

  • Atsmegiorgis, Cheru;Kim, Jongtae;Yoon, Sanghoo
    • Journal of the Korean Data and Information Science Society
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    • 제27권6호
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    • pp.1661-1671
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    • 2016
  • Risk analysis is a systematic study of uncertainties and risks we encounter in business, engineering, public policy, and many other areas. Value at Risk (VaR) is one of the most widely used risk measurements in risk management. In this paper, the Korean Composite Stock Price Index data has been utilized to model the VaR employing the classical ARMA (1,1)-GARCH (1,1) models with normal, t, generalized hyperbolic, and generalized pareto distributed errors. The aim of this paper is to compare the performance of each model in estimating the VaR. The performance of models were compared in terms of the number of VaR violations and Kupiec exceedance test. The GARCH-GPD likelihood ratio unconditional test statistic has been found to have the smallest value among the models.

Comparison Density Representation of Traditional Test Statistics for the Equality of Two Population Proportions

  • Jangsun Baek
    • Communications for Statistical Applications and Methods
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    • 제2권1호
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    • pp.112-121
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    • 1995
  • Let $p_1$ and $p_2$ be the proportions of two populations. To test the hypothesis $H_0 : p_1 = p_2$, we usually use the $x^2$ statistic, the large sample binomial statistic Z, and the Generalized Likelihood Ratio statistic-2log $\lambda$developed based on different mathematical rationale, respectively. Since testing the above hypothesis is equivalent to testing whether two populations follow the common Bernoulli distribution, one may also test the hypothesis by comparing 1 with the ratio of each density estimate and the hypothesized common density estimate, called comparison density, which was devised by Parzen(1988). We show that the above traditional test statistics ate actually estimating the measure of distance between the true densities and the common density under $H_0$ by representing them with the comparison density.

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집락자료의 분할표에서 독립성검정 (Testing Independence in Contingency Tables with Clustered Data)

  • 정광모;이현영
    • 응용통계연구
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    • 제17권2호
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    • pp.337-346
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    • 2004
  • 랜덤표본에 관한 이원분할표의 독립성검정에는 통상 피어슨의 카이제곱적합도검정과 우도비검정을 사용한다. 그러나 랜덤표본이 아닌 집락자료에 관한 분할표의 경우에는 이들 검정법은 잘못된 결과를 나타낸다. 이러한 경우에는 공변량의 고정효과 외에 집락에 따른 변량효과를 함께 포함하는 일반화선형혼합모형을 고려함으로써 집락간의 이질성과 집락내의 종속성을 반영할 수 있다. 본 연구에서는 집락자료의 분할표에 대한 일반화선형혼합모형을 소개하고 실례를 통하여 이들 모형의 적합에 대해 논의한다.

비정규 잡음 환경에서 협력 무선인지 네트워크를 위한 순서 기반 스펙트럼 센싱 기법 (An Order Statistic-Based Spectrum Sensing Scheme for Cooperative Cognitive Radio Networks in Non-Gaussian Noise Environments)

  • 조형원;이영포;윤석호;배석능;이광억
    • 한국통신학회논문지
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    • 제37A권11호
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    • pp.943-951
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    • 2012
  • 본 논문에서는 비정규 충격성 잡음 환경에서 협력 무선인지 네트워크를 위한 순서 기반 스펙트럼 센싱 기법을 제안한다. 구체적으로는 잡음을 이변수 등방형 대칭 알파 안정 (bivariate isotropic symmetric ${\alpha}$-stable) 분포를 따르는 것으로 모형화하고, 그에 알맞은 관측 샘플의 순서와 일반화된 우도비 검정 기반 협력 스펙트럼 센싱 기법을 제안한다. 모의실험을 통해 비정규 잡음 환경에서 제안한 기법이 기존의 기법에 비해 더 좋은 스펙트럼 센싱성능을 가짐을 보인다.