• Title/Summary/Keyword: 로그 우도비

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Likelihood based inference for the ratio of parameters in two Maxwell distributions (두 개의 맥스웰분포의 모수비에 대한 우도함수 추론)

  • Kang, Sang-Gil;Lee, Jeong-Hee;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.1
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    • pp.89-98
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    • 2012
  • In this paper, the ratio of parameters in two independent Maxwell distributions is parameter of interest. We proposed test statistics, which converge to standard normal distribution, based on likelihood function. The exact distribution for testing the ratio is hard to obtain. We proposed the signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic for testing the ratio. Through simulation, we show that the modified signed log-likelihood ratio statistic converges faster than signed log-likelihood ratio statistic to standard normal distribution. We compare two statistics in terms of type I error and power. We give an example using real data.

Screening and Clustering for Time-course Yeast Microarray Gene Expression Data using Gaussian Process Regression (효모 마이크로어레이 유전자 발현데이터에 대한 가우시안 과정 회귀를 이용한 유전자 선별 및 군집화)

  • Kim, Jaehee;Kim, Taehoun
    • The Korean Journal of Applied Statistics
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    • v.26 no.3
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    • pp.389-399
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    • 2013
  • This article introduces Gaussian process regression and shows its application with time-course microarray gene expression data. Gene screening for yeast cell cycle microarray expression data is accomplished with a ratio of log marginal likelihood that uses Gaussian process regression with a squared exponential covariance kernel function. Gaussian process regression fitting with each gene is done and shown with the nine top ranking genes. With the screened data the Gaussian model-based clustering is done and its silhouette values are calculated for cluster validity.

CUSUM charts for monitoring type I right-censored lognormal lifetime data (제1형 우측중도절단된 로그정규 수명 자료를 모니터링하는 누적합 관리도)

  • Choi, Minjae;Lee, Jaeheon
    • The Korean Journal of Applied Statistics
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    • v.34 no.5
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    • pp.735-744
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    • 2021
  • Maintaining the lifetime of a product is one of the objectives of quality control. In real processes, most samples are constructed with censored data because, in many situations, we cannot measure the lifetime of all samples due to time or cost problems. In this paper, we propose two cumulative sum (CUSUM) control charting procedures to monitor the mean of type I right-censored lognormal lifetime data. One of them is based on the likelihood ratio, and the other is based on the binomial distribution. Through simulations, we evaluate the performance of the two proposed procedures by comparing the average run length (ARL). The overall performance of the likelihood ratio CUSUM chart is better, especially this chart performs better when the censoring rate is low and the shape parameter value is small. Conversely, the binomial CUSUM chart is shown to perform better when the censoring rate is high, the shape parameter value is large, and the change in the mean is small.

Performance Analysis Based On Log-Likelihood Ratio in Orthogonal Code Hopping Multiplexing Systems Using Multiple Antennas (다중 안테나를 사용한 직교 부호 도약 다중화 시스템에서 로그 우도비 기반 성능 분석)

  • Jung, Bang-Chul;Sung, Kil-Young;Shin, Won-Yong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.12
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    • pp.2534-2542
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    • 2011
  • In this paper, we show that performance can be improved by using multiple antennas in the conventional orthogonal code hopping multiplexing (OCHM) scheme, which was proposed for accommodating a larger number of users with low channel activities than the number of orthogonal codewords used in code division multiple access (CDMA)-based communication systems through downlink statistical multiplexing. First, we introduce two different types of OCHM systems together with orthogonal codeword allocation strategies, and then derive their mathematical expression for log-likelihood ratio (LLR) values according to the two different schemes. Next, when a turbo encoder based on the LLR computation is used, we evaluate performance on the frame error rate (FER) for the aformentioned OCHM system. For comparison, we also show performance for the existing symbol mapping method using multiple antennas, which was used in 3GPP standards. As a result, it is shown that our OCHM system with multiple antennas based on the proposed orthogonal codeword allocation strategy leads to performance gain over the conventional system---energy required to satisfy a target FER is significantly reduced.

Threshold estimation for the composite lognormal-GPD models (로그-정규분포와 파레토 합성 분포의 임계점 추정)

  • Kim, Bobae;Noh, Jisuk;Baek, Changryong
    • The Korean Journal of Applied Statistics
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    • v.29 no.5
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    • pp.807-822
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    • 2016
  • The composite lognormal-GPD models (LN-GPD) enjoys both merits from log-normality for the body of distribution and GPD for the thick tailedness of the observation. However, in the estimation perspective, LN-GPD model performs poorly due to numerical instability. Therefore, a two-stage procedure, that estimates threshold first then estimates other parameters later, is a natural method to consider. This paper considers five nonparametric threshold estimation methods widely used in extreme value theory and compares their performance in LN-GPD parameter estimation. A simulation study reveals that simultaneous maximum likelihood estimation performs good in threshold estimation, but very poor in tail index estimation. However, the nonparametric method performs good in tail index estimation, but introduced bias in threshold estimation. Our method is illustrated to the service time of an Israel bank call center and shows that the LN-GPD model fits better than LN or GPD model alone.

An Analysis on Vehicle Accident Factors of Intersections using Random Effects Tobit Regression Model (Random Effects Tobit 회귀모형을 이용한 교차로 교통사고 요인 분석)

  • Lee, Sang Hyuk;Lee, Jung-Beom
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.1
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    • pp.26-37
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    • 2017
  • The study is to develop safety performance functions(SPFs) for urban intersections using random effects Tobit regression model and to analyze correlations between crashes and factors. Also fixed effects Tobit regression model was estimated to compare and analyze model validation with random effects model. As a result, AADT, speed limits, number of lanes, land usage, exclusive right turn lanes and front traffic signal were found to be significant. For comparing statistical significance between random and fixed effects model, random effects Tobit regression model of total crash rate could be better statistical significance with $R^2_p$ : 0.418, log-likelihood at convergence: -3210.103, ${\rho}^2$: 0.056, MAD: 19.533, MAPE: 75.725, RMSE: 26.886 comparing with $R^2_p$ : 0.298, log-likelihood at convergence: -3276.138, ${\rho}^2$: 0.037, MAD: 20.725, MAPE: 82.473, RMSE: 27.267 for the fixed model. Also random effects Tobit regression model of injury crash rate has similar results of model statistical significant with random effects Tobit regression model.

Improvement of Rating Curve Fitting Considering Variance Function with Pseudo-likelihood Estimation (의사우도추정법에 의한 분산함수를 고려한 수위-유량 관계 곡선 산정법 개선)

  • Lee, Woo-Seok;Kim, Sang-Ug;Chung, Eun-Sung;Lee, Kil-Seong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2008.05a
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    • pp.1770-1773
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    • 2008
  • 수위-유량 관계 곡선식에 포함되어져 있는 매개변수를 추정하기 위해 많이 사용되는 로그선형 회귀분석은 잔차의 비등분산성(heterocesdascity)을 고려하지 못하므로 본 연구에서는 의사우도추정법(Pseudo-likelihood Estimation, P-LE)에 의해 분산함수를 추정하고 이와 함께 회귀계수를 추정할 수 있는 방법을 제시하였다. 이 과정에서 제시된 회귀잔차를 최소화하기 위하여 SA(simulated annealing)이라는 전역 최적화 알고리즘을 적용하였다. 또한 수위-유량 관계 곡선식은 단면 등의 영향으로 인해 구간에 따라 각각 다르게 구축되어져야 하므로 이를 보다 객관적으로 판단하고 분리 위치를 정확히 추정하기 위하여 Heaviside 함수를 의사우도함수에 포함시켜 결과를 추정하도록 하였으며, 2개의 구간을 가지는 유량자료를 이용하여 제시된 방법의 합리성을 통계적으로 실험하였다. 이와 같이 통계적 실험을 통해 제시된 방법들이 기존 방법과 비교하여 가질 수 있는 장점을 파악하였으며, 제시된 방법들을 금강유역 5개 지점에서 대해 수행하여 효율성을 검증하였다.

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Likelihood based inference for the shape parameter of Pareto Distribution

  • Lee, Jae-Un;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.4
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    • pp.1173-1181
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    • 2008
  • In this paper, when the parameter of interest is the shape parameter in Pareto distribution, we develop likelihood based inference for this parameter. Specially, we develop signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic for the shape parameter. It is well-known that as sample size grows, the modified signed log-likelihood ratio statistic converges to standard normal distribution faster than the signed log-likelihood ratio statistic. But the computation of the modified signed log-likelihood statistic is hard or even impossible when the sufficient statistics and the ancillary statistics are not clear. In this case, one can consider an approximation to the modified signed log-likelihood statistic. Specially, when the parameter of interest is informationally orthogonal to the nuisance parameters, we propose the approximate modified signed log-likelihood statistic. Through simulation, we investigate the performances of the proposed statistics with the signed log-likelihood statistic.

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Statistical Voice Activity Detection Using Probabilistic Non-Negative Matrix Factorization (확률적 비음수 행렬 인수분해를 사용한 통계적 음성검출기법)

  • Kim, Dong Kook;Shin, Jong Won;Kwon, Kisoo;Kim, Nam Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.8
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    • pp.851-858
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    • 2016
  • This paper presents a new statistical voice activity detection (VAD) based on the probabilistic interpretation of nonnegative matrix factorization (NMF). The objective function of the NMF using Kullback-Leibler divergence coincides with the negative log likelihood function of the data if the distribution of the data given the basis and encoding matrices is modeled as Poisson distributions. Based on this probabilistic NMF, the VAD is constructed using the likelihood ratio test assuming that speech and noise follow Poisson distributions. Experimental results show that the proposed approach outperformed the conventional Gaussian model-based and NMF-based methods at 0-15 dB signal-to-noise ratio simulation conditions.

A Study on Developing Crash Prediction Model for Urban Intersections Considering Random Effects (임의효과를 고려한 도심지 교차로 교통사고모형 개발에 관한 연구)

  • Lee, Sang Hyuk;Park, Min Ho;Woo, Yong Han
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.14 no.1
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    • pp.85-93
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    • 2015
  • Previous studies have estimated crash prediction models with the fixed effect model which assumes the fixed value of coefficients without considering characteristics of each intersections. However the fixed effect model would estimate under estimation of the standard error resulted in over estimation of t-value. In order to overcome these shortcomings, the random effect model can be used with considering heterogeneity of AADT, geometric information and unobserved factors. In this study, data collections from 89 intersections in Daejeon and estimates of crash prediction models were conducted using the random and fixed effect negative binomial regression model for comparison and analysis of two models. As a result of model estimates, AADT, speed limits, number of lanes, exclusive right turn pockets and front traffic signal were found to be significant. For comparing statistical significance of two models, the random effect model could be better statistical significance with -1537.802 of log-likelihood at convergence comparing with -1691.327 for the fixed effect model. Also likelihood ration value was computed as 0.279 for the random effect model and 0.207 for the fixed effect model. This mean that the random effect model can be improved for statistical significance of models comparing with the fixed effect model.