• Title/Summary/Keyword: partial likelihood

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Parameter Estimation for a Hilbert Space-valued Stochastic Differential Equation ?$\pm$

  • Kim, Yoon-Tae;Park, Hyun-Suk
    • Journal of the Korean Statistical Society
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    • v.31 no.3
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    • pp.329-342
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    • 2002
  • We deal with asymptotic properties of Maximum Likelihood Estimator(MLE) for the parameters appearing in a Hilbert space-valued Stochastic Differential Equation(SDE) and a Stochastic Partial Differential Equation(SPDE). In paractice, the available data are only the finite dimensional projections to the solution of the equation. Using these data we obtain MLE and consider the asymptotic properties as the dimension of projections increases. In particular we explore a relationship between the conditions for the solution and asymptotic properties of MLE.

An Adaptive Partial Response Equalizer Using Branch Metrics of Viterbi Trellis for Optical Recording Systems (고밀도 광 기록 장치에서 비터비 트렐리스의 가지 메트릭을 이용한 부분 응답 적응 등화기)

  • Lee, Kyu-Suk;Lee, Joo-Hyun;Lee, Jae-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.9C
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    • pp.871-876
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    • 2005
  • In this paper, we propose an improved partial response maximum likelihood (PRML) detection scheme that has an adaptive equalizer and can be applied in the asymmetric optical recording system with high-density. We confirmed that the proposed PRML detector improves detection performance. In addition, we implemented the detector by Verilog HDL. The adaptive equalizer is composed of tap coefficient updating unit using LMS algorithn and FIR filter. FIR filter is implemented by the transposed direct form architecture for high speed operation. Viterbi detector is implemented by the register exchange method.

Low complexity hybrid layered tabu-likelihood ascent search for large MIMO detection with perfect and estimated channel state information

  • Sourav Chakraborty;Nirmalendu Bikas Sinha;Monojit Mitra
    • ETRI Journal
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    • v.45 no.3
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    • pp.418-432
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    • 2023
  • In this work, we proposed a low-complexity hybrid layered tabu-likelihood ascent search (LTLAS) algorithm for large multiple-input multiple-output (MIMO) system. The conventional layered tabu search (LTS) approach involves many partial reactive tabu searches (RTSs), and each RTS requires an initialization and searching phase. In the proposed algorithm, we restricted the upper limit of the number of RTS operations. Once RTS operations exceed the limit, RTS will be replaced by low-complexity likelihood ascent search (LAS) operations. The block-based detection approach is considered to maintain a higher signal-to-noise ratio (SNR) detection performance. An efficient precomputation technique is derived, which can suppress redundant computations. The simulation results show that the bit error rate (BER) performance of the proposed detection method is close to the conventional LTS method. The complexity analysis shows that the proposed method has significantly lower computational complexity than conventional methods. Also, the proposed method can reduce almost 50% of real operations to achieve a BER of 10-3.

Comparison of Change-point Estimators in Hazard Rate Models

  • Kim, Jaehee
    • Communications for Statistical Applications and Methods
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    • v.9 no.3
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    • pp.753-763
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    • 2002
  • When there is one change-point in the hazard rate model, a change-point estimator with the partial score process is suggested and compared with the previously developed estimators. The limiting distribution of the partial score process we used is a function of the Brownian bridge. Simulation study gives the comparison of change-point estimators.

On the analysis of multistate survival data using Cox's regression model (Cox 회귀모형을 이용한 다중상태의 생존자료분석에 관한 연구)

  • Sung Chil Yeo
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.53-77
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    • 1994
  • In a certain stochastic process, Cox's regression model is used to analyze multistate survival data. From this model, the regression parameter vectors, survival functions, and the probability of being in response function are estimated based on multistate Cox's partial likelihood and nonparametric likelihood methods. The asymptotic properties of these estimators are described informally through the counting process approach. An example is given to likelihood the results in this paper.

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Monotone Local Linear Quasi-Likelihood Response Curve Estimates

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.273-283
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    • 2006
  • In bioassay, the response curve is usually assumed monotone increasing, but its exact form is unknown, so it is very difficult to select the proper functional form for the parametric model. Therefore, we should probably use the nonparametric regression model rather than the parametric model unless we have at least the partial information about the true response curve. However, it is well known that the nonparametric regression estimate is not necessarily monotone. Therefore the monotonizing transformation technique is of course required. In this paper, we compare the finite sample properties of the monotone transformation methods which can be applied to the local linear quasi-likelihood response curve estimate.

Low-Complexity Detection Techniques for High-Density DVD Systems (고밀도 DVD시스템을 위한 저 복잡도 검출 기법)

  • Cho, Han-Gyu;Woo, Choong-Chae;Joo, Man-Sic;Kang, Chang-Eon;Hong, Dae-Sik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.10A
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    • pp.1000-1010
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    • 2002
  • Partial response maximum-likelihood (PRML) and fixed-delay tree search with decision feedback (FDTS/DF) yield a sub-optimum performance in storage systems. However, they suffer from the inevitable complexity problems. this paper focuses on detection schemes to overcome the drawbacks of the sequence detections by exploiting minimum run-length d=2. It is expected that the proposed systems yield substantial reductions of both processing speed and receiver complexity. When combined with a decision feedback equalization (DFE), they prove to keep pace with the FDTS/DF with ${\tau}$=2 and even outperform the PR(1111)ML at normalized density S>5.6.

A New Subspace Search-based Method for MIMO Systems (MIMO 시스템에서 부분 검색 공간 기반의 검파기법)

  • Nam, Sang-Ho;Ko, Kyun-Byoung;Hong, Dae-Sik
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.48 no.5
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    • pp.25-32
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    • 2011
  • In this paper, we propose a subspace search-based detector (SSD) with low-complexity to achieve near optimal performance for multiple-input multiple-output systems. As an effective solution to reduce the prohibitive computational complexity of the optimal maximum likelihood detector, a partial candidate symbol vector is generated through a partitioned search space but not the entire search space. In addition, based on a partial candidate symbol vector, an ensemble candidate symbol vector generation considering the whole search space is introduced to produce a near optimal solution. As a result, the proposed SSD achieves near-maximum-likelihood performance while having a significantly reduced computational complexity.

Simultaneous Tests with Combining Functions under Normality

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.22 no.6
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    • pp.639-646
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    • 2015
  • We propose simultaneous tests for mean and variance under the normality assumption. After formulating the null hypothesis and its alternative, we construct test statistics based on the individual p-values for the partial tests with combining functions and derive the null distributions for the combining functions. We then illustrate our procedure with industrial data and compare the efficiency among the combining functions with individual partial ones by obtaining empirical powers through a simulation study. A discussion then follows on the intersection-union test with a combining function and simultaneous confidence region as a simultaneous inference; in addition, we discuss weighted functions and applications to the statistical quality control. Finally we comment on nonparametric simultaneous tests.

Empirical Comparisons of Disparity Measures for Partial Association Models in Three Dimensional Contingency Tables

  • Jeong, D.B.;Hong, C.S.;Yoon, S.H.
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.135-144
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    • 2003
  • This work is concerned with comparison of the recently developed disparity measures for the partial association model in three dimensional categorical data. Data are generated by using simulation on each term in the log-linear model equation based on the partial association model, which is a proposed method in this paper. This alternative Monte Carlo methods are explored to study the behavior of disparity measures such as the power divergence statistic I(λ), the Pearson chi-square statistic X$^2$, the likelihood ratio statistic G$^2$, the blended weight chi-square statistic BWCS(λ), the blended weight Hellinger distance statistic BWHD(λ), and the negative exponential disparity statistic NED(λ) for moderate sample sizes. We find that the power divergence statistic I(2/3) and the blended weight Hellinger distance family BWHD(1/9) are the best tests with respect to size and power.