• 제목/요약/키워드: Parametric Density Estimation

검색결과 50건 처리시간 0.023초

Kernel Inference on the Inverse Weibull Distribution

  • Maswadah, M.
    • Communications for Statistical Applications and Methods
    • /
    • 제13권3호
    • /
    • pp.503-512
    • /
    • 2006
  • In this paper, the Inverse Weibull distribution parameters have been estimated using a new estimation technique based on the non-parametric kernel density function that introduced as an alternative and reliable technique for estimation in life testing models. This technique will require bootstrapping from a set of sample observations for constructing the density functions of pivotal quantities and thus the confidence intervals for the distribution parameters. The performances of this technique have been studied comparing to the conditional inference on the basis of the mean lengths and the covering percentage of the confidence intervals, via Monte Carlo simulations. The simulation results indicated the robustness of the proposed method that yield reasonably accurate inferences even with fewer bootstrap replications and it is easy to be used than the conditional approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.

Distributed Channel Allocation Using Kernel Density Estimation in Cognitive Radio Networks

  • Ahmed, M. Ejaz;Kim, Joo Seuk;Mao, Runkun;Song, Ju Bin;Li, Husheng
    • ETRI Journal
    • /
    • 제34권5호
    • /
    • pp.771-774
    • /
    • 2012
  • Typical channel allocation algorithms for secondary users do not include processes to reduce the frequency of switching from one channel to another caused by random interruptions by primary users, which results in high packet drops and delays. In this letter, with the purpose of decreasing the number of switches made between channels, we propose a nonparametric channel allocation algorithm that uses robust kernel density estimation to effectively schedule idle channel resources. Experiment and simulation results demonstrate that the proposed algorithm outperforms both random and parametric channel allocation algorithms in terms of throughput and packet drops.

모수적·비모수적 입력모델링 기법을 이용한 신뢰성 해석 (Reliability Analysis Using Parametric and Nonparametric Input Modeling Methods)

  • 강영진;홍지민;임오강;노유정
    • 한국전산구조공학회논문집
    • /
    • 제30권1호
    • /
    • pp.87-94
    • /
    • 2017
  • 신뢰성 해석 및 신뢰성기반 최적설계는 불확실성을 고려한 확률변수를 입력 값으로 요구하며, 확률변수는 모수적 비모수적 통계모델링 방법을 사용하여 확률분포함수의 형태로 정량화 된다. 신뢰성 해석과 같은 통계적 해석은 입력되는 확률분포함수의 특성이 결과값에 영향을 미치게 되며, 확률분포함수는 통계모델링 방법에 따라 다른 형태를 가지게 된다. 본 연구에서는 모수적 통계모델링 방법인 순차적 통계모델링 방법과 비모수적 방법인 커널밀도추정을 사용하여 데이터의 개수에 따른 통계모델링의 결과를 분석하였다. 또한 수치예제를 통해 두 가지 기법에 따른 신뢰성 해석의 결과를 분석하였고, 데이터의 개수에 따른 적절한 기법을 제안하였다.

Bootstrap methods for long-memory processes: a review

  • Kim, Young Min;Kim, Yongku
    • Communications for Statistical Applications and Methods
    • /
    • 제24권1호
    • /
    • pp.1-13
    • /
    • 2017
  • This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

On the Selection of Bezier Points in Bezier Curve Smoothing

  • Kim, Choongrak;Park, Jin-Hee
    • 응용통계연구
    • /
    • 제25권6호
    • /
    • pp.1049-1058
    • /
    • 2012
  • Nonparametric methods are often used as an alternative to parametric methods to estimate density function and regression function. In this paper we consider improved methods to select the Bezier points in Bezier curve smoothing that is shown to have the same asymptotic properties as the kernel methods. We show that the proposed methods are better than the existing methods through numerical studies.

개선된 ESPRIT 알고리즘을 이용한 퍼진 신호의 신호도착방향 추정 (Estimation of Distributed Signal's Direction of Arrival Using Advanced ESPRIT Algorithm)

  • 정성훈;이동욱
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
    • /
    • pp.703-705
    • /
    • 1999
  • In this paper, we introduce the direction of arrival(DOA) estimation of distributed signal based on the improved ESPRIT algorithm. Most research on the estimation of DOA has been performed based on the assumption that the signal sources are point sources. However, we consider a two-dimensional distributed signal source model using improved ESPRIT algorithm. In the distributed signal source model, a source is represented by two parameters, the azimuth angle and elevation angle. We address the estimation of the elevation and azimuth angles of distributed sources based on the parametric source modeling in the three-dimensional space with two uniform linear arrays. The array output vector is obtained by integrating a steering vector over all direction of arrival with the weighting of a distributed source density function. We also develop an efficient estimation procedures that can reduce the computational complexity. Some examples are shown to demonstrate explicity the estimation procedures under the distributed signal source model.

  • PDF

Economic performance of cable supported bridges

  • Sun, Bin;Zhang, Liwen;Qin, Yidong;Xiao, Rucheng
    • Structural Engineering and Mechanics
    • /
    • 제59권4호
    • /
    • pp.621-652
    • /
    • 2016
  • A new cable-supported bridge model consisting of suspension parts, self-anchored cable-stayed parts and earth-anchored cable-stayed parts is presented. The new bridge model can be used for suspension bridges, cable-stayed bridges, cable-stayed suspension bridges, and partially earth-anchored cable-stayed bridges by varying parameters. Based on the assumption that each structural member is in either an axial compressive or tensile state, and the stress in each member is equal to the allowable stress of the material, the material quantity for each component is calculated. By introducing the unit cost of each type of material, the estimation formula for the cost of the new bridge model is developed. Numerical examples show that the results from the estimation formula agree well with that from the real projects. The span limit of cable supported bridge depends on the span-to-height ratio and the density-to-strength ratio of cables. Finally, a parametric study is illustrated aiming at the relations between three key geometrical parameters and the cost of the bridge model. The optimization of the new bridge model indicates that the self-anchored cable-stayed part is always the dominant part with the consideration of either the lowest total cost or the lowest unit cost. It is advisable to combine all three mentioned structural parts in super long span cable supported bridges to achieve the most excellent economic performance.

Analysis of ASEAN's Stock Returns and/or Volatility Distribution under the Impact of the Chinese EPU: Evidence Based on Conditional Kernel Density Approach

  • Mohib Ur Rahman;Irfan Ullah;Aurang Zeb
    • East Asian Economic Review
    • /
    • 제27권1호
    • /
    • pp.33-60
    • /
    • 2023
  • This paper analyzes the entire distribution of stock market returns/volatility in five emerging markets (ASEAN5) and figures out the conditional distribution of the CHI_EPU index. The aim is to examine the impact of CHI_EPU on the stock returns/volatility density of ASEAN5 markets. It also examined whether changes in CHI_EPU explain returns at higher or lower points (abnormal returns). This paper models the behaviour of stock returns from March 2011 to June 2018 using a non-parametric conditional density estimation approach. The results indicate that CHI_EPU diminishes stock returns and augments volatility in ASEAN5 markets, except for Malaysia, where it affects stock returns positively. The possible reason for this positive impact is that EPU is not the leading factor reducing Malaysian stock returns; but, other forces, such as dependency on other countries' stock markets and global factors, may have a positive impact on stock returns (Bachmann and Bayer, 2013). Thus, the risk of simultaneous investment in Chinese and ASEAN5 stock markets, except Malaysia, is high. Further, the degree of this influence intensifies at extreme high/low intervals (positive/negative tails). The findings of this study have significant implications for investors, policymakers, market agents, and analysts of ASEAN5.

An Empirical Study on Dimension Reduction

  • Suh, Changhee;Lee, Hakbae
    • Journal of the Korean Data Analysis Society
    • /
    • 제20권6호
    • /
    • pp.2733-2746
    • /
    • 2018
  • The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.

커널 밀도 추정을 이용한 Fuzzy C-Means의 초기화 (Initialization of Fuzzy C-Means Using Kernel Density Estimation)

  • 허경용;김광백
    • 한국정보통신학회논문지
    • /
    • 제15권8호
    • /
    • pp.1659-1664
    • /
    • 2011
  • Fuzzy C-Means (FCM)는 군집화를 위해 널리 사용되는 알고리듬 중 하나로 다양한 응용 분야에서 성공적으로 사용되어 왔다. 하지만 FCM은 여러 가지 단점을 가지고 있으며 초기 원형 설정이 그 중 하나이다. FCM은 국부 최적해에 수렴하므로 초기 원형 설정에 따라 군집화의 결과가 달라진다. 따라서 초기 원형의 설정은 군집화 결과 향상을 위해 중요하다. 이 논문에서는 이러한 FCM의 초기 원형 설정 문제를 해결하는 방안으로 커널 밀도 추정을 활용하는 방법을 제안한다. 커널 밀도 추정은 비모수적 분포들에도 사용할 수 있어 국부적인 데이터 밀도 추정에 유용하다. 제안한 방법에서는 커널 밀도 추정을 수행한 후 밀도가 높은 지역에 클러스터의 초기 원형을 설정하고 원형이 설정된 영역의 밀도를 감소시키는 과정을 반복함으로써 효율적으로 초기 원형을 선택할 수 있다. 제안된 방법이 일반적으로 사용되는 무작위 초기화 방법에 비해 효율적이라는 사실은 실험 결과를 통해 확인할 수 있다.