• Title/Summary/Keyword: unimodality

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THE UNIMODALITY OF THE r3-CRANK OF 3-REGULAR OVERPARTITIONS

  • Robert XiaoJian Hao;Erin YiYing Shen
    • Bulletin of the Korean Mathematical Society
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    • v.61 no.3
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    • pp.621-635
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    • 2024
  • An 𝑙-regular overpartition of n is an overpartition of n with no parts divisible by 𝑙. Recently, the authors introduced a partition statistic called r𝑙-crank of 𝑙-regular overpartitions. Let Mr𝑙(m, n) denote the number of 𝑙-regular overpartitions of n with r𝑙-crank m. In this paper, we investigate the monotonicity property and the unimodality of Mr3(m, n). We prove that Mr3(m, n) ≥ Mr3(m, n - 1) for any integers m and n ≥ 6 and the sequence {Mr3(m, n)}|m|≤n is unimodal for all n ≥ 14.

ON THE FAILURE OF GORENSTEINESS FOR THE SEQUENCE (1, 125, 95, 77, 70, 77, 95, 125, 1)

  • Ahn, Jeaman
    • Journal of the Chungcheong Mathematical Society
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    • v.28 no.4
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    • pp.537-543
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    • 2015
  • In [9], the authors determine an infinite class of non-unimodal Gorenstein sequence, which includes the example $$\bar{h}_1\text{ = (1, 125, 95, 77, 71, 77, 95, 125, 1)}$$. They raise a question whether there is a Gorenstein algebra with Hilbert function $$\bar{h}_2\text{= (1, 125, 95, 77, 70, 77, 95, 125, 1)}$$, which has remained an open question. In this paper, we prove that there is no Gorenstein algebra with Hilbert function $\bar{h}_2$.

Properties of the Poisson-power Function Distribution

  • Kim, Joo-Hwan
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.166-175
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    • 1995
  • When a neutral particle beam(NPB) aimed at the object and receive a small number of neutron signals at the detector without any errors, it obeys Poisson law. Under the two assumptions that neutral particle scattering distribution and aiming errors have a circular Gaussian distributions that neutral particle scattering distribution and aiming errors have a circular Gaussian distribution respectively, an exact probability distribution of neutral particles vecomes a Poisson-power function distribution. We study and prove some properties, such as limiting distribution, unimodality, stochastical ordering, computational recursion fornula, of this distribution. We also prove monotone likelihood ratio(MLR) property of this distribution. Its MLR property can be used to find a criteria for the hypothesis testing problem.

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The Region of Positivity and Unimodality in the Truncated Series of a Nonparametric Kernel Density Estimator

  • Gupta, A.K.;Im, B.K.K.
    • Journal of the Korean Statistical Society
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    • v.10
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    • pp.140-144
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    • 1981
  • This paper approximates to a kernel density estimate by a truncated series of expansion involving Hermite polynomials, since this could ease the computing burden involved in the kernel-based density estimation. However, this truncated series may give a multimodal estimate when we are estiamting unimodal density. In this paper we will show a way to insure the truncated series to be positive and unimodal so that the approximation to a kernel density estimator would be maeningful.

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A General Class of Acceptance-Rejection Distributions and Its Applications

  • Kim, Hea-Jung;Yum, Joon-Keun;Lee, Yung-Seop;Cho, Chun-Ho;Chung, Hyo-Sang
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.10a
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    • pp.19-30
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    • 2003
  • In this paper we present a new family of distributions that allows a continuous variation not only from normality to non-normality but also from unimodality to bimodality. Its properties are especially useful in studying and making inferences about models involving the univariate truncated normal distribution. The properties of the family and its applications are given.

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Climate Prediction by a Hybrid Method with Emphasizing Future Precipitation Change of East Asia

  • Lim, Yae-Ji;Jo, Seong-Il;Lee, Jae-Yong;Oh, Hee-Seok;Kang, Hyun-Suk
    • The Korean Journal of Applied Statistics
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    • v.22 no.6
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    • pp.1143-1152
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    • 2009
  • A canonical correlation analysis(CCA)-based method is proposed for prediction of future climate change which combines information from ensembles of atmosphere-ocean general circulation models(AOGCMs) and observed climate values. This paper focuses on predictions of future climate on a regional scale which are of potential economic values. The proposed method is obtained by coupling the classical CCA with empirical orthogonal functions(EOF) for dimension reduction. Furthermore, we generate a distribution of climate responses, so that extreme events as well as a general feature such as long tails and unimodality can be revealed through the distribution. Results from real data examples demonstrate the promising empirical properties of the proposed approaches.

Air-Data Estimation for Air-Breathing Hypersonic Vehicles

  • Kang, Bryan-Heejin
    • Transactions on Control, Automation and Systems Engineering
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    • v.1 no.1
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    • pp.75-86
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    • 1999
  • An air-data estimator for generic air-breathing hypersonic vehicles (AHSVs) is developed and demonstrated with an example vehicle configuration. The AHSV air-data estimation strategy emphasized improvement of the angle of attack estimate accuracy to a degree necessitated by the stringent operational requirements of the air-breathing propulsion. the resulting estimation problem involves highly nonlinear diffusion process (propagation); consequently, significant distortion of a posteriori conditional density is suspected. A simulation based statistical analysis tool is developed to characterize the nonlinear diffusion process. The statistical analysis results indicate that the diffusion process preserves the symmetry and unimodality of initial probability density shape state variables, and provide the basis for applicability of an Extended Kalman Filter (EKF). An EKF is designed for the AHSV air-data system and the air data estimation capabilities are demonstrated.

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Genetic Algorithms as Optimisation Tools and Their Applications (최적화기법으로서의 유전알고리즘과 그 응용)

  • 진강규;하주식
    • Journal of Advanced Marine Engineering and Technology
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    • v.21 no.2
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    • pp.108-116
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    • 1997
  • 유전알고리즘은 진화원리에서 발견된 몇몇 특징들을 컴퓨터 알고리즘과 결합시켜 복잡한 최적화 문제를 해결하려는 도구로서 1975년 미국의 Holland 교수에 의해 처음으로 개발되었다. 주어진 문제에서 탐색환경이 다변수 또는 다봉(multi-modal)이 되어 대단히 복잡하거나 또는 부분적으로 알려질 경우는, 구배(gradient)에 기초한 재래식 방법을 사용하여 최적화하는 것은 매우 어렵게 되고 경우에 따라서는 불가능할 수도 있다. 이러한 이유로 유전알고리즘과 같은 강인한 탐색법이 요구된다. 유전알고리즘의 장점은 연속성(continuity), 미분가능성(differentiability), 단봉성(unimodality) 등과 같이 탐색공간에 대한 제약으로부터 자유롭다는 것이다. 다시 말하면 목적함수 외 탐색공간에 대한 사전지식을 필요로 하지 않고, 매우 크고 복잡한 공간일지라도 전역해 쪽으로 수렴해 갈수 있다는 것이다. 이러한 특성 때문에 유전알고리즘은 실제 환경에서 많은 복잡한 최적화 문제를 해결하는 방법으로 인정을 받고 있으며, 함수의 최적화, 신경회로망의 학습, 동적시스템의 식별및 제어, 신호처리등 여러 분야에 성공적으로 응용되고 있다. 이러한 중요성에 비해 유전알고리즘에 대한 연구는 국내적으로는 아직 미진한 수준이나 최근 이에 대한 관심이 고조되고 있으며, 또한 그 응용분야도 점점 넓어져 이론 개발과 실질적인 응용에 확산되리라 생각된다. 따라서 본 해설기사는 유전알고리즘의 원리와 응용 사례를 살펴봄으로서 최적화 문제를 해결하려는 독자들에게 조금이나마 도움을 주고자 한다.

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Determination of Optimal Replacement Period for A Multicomponent System Consider with Failure Types (고장형태(故障形態)를 고려(考慮)한 다부품장비(多部品裝備)의 최적교환시기(最適交換時期) 결정(決定))

  • Lee, Seung-Jun;Gang, Chang-Uk;Hwang, Ui-Cheol
    • Journal of Korean Society for Quality Management
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    • v.19 no.2
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    • pp.117-124
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    • 1991
  • In this paper, it is assumed that a system is composed of an essential unit and a nonessential unit. During the running of the system, an essential unit is replaced at periodic replacement time T or at nth failure of essential unit whichever occurs first. Nonessential unit is replaced at its failure and at the replacement of essential unit. This paper derive optimal replacement period which minmises the total expected cost for replacement. The unimodality of totoal maintenance cost function is proved under the assumption that hazard rate of each component is continuous and monotone increasing failure rate(IFR). Based on this condition, it is shown that the optimal replacement period is finite and unique.

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Families of Distributions Arising from Distributions of Ordered Data

  • Ahmadi, Mosayeb;Razmkhah, M.;Mohtashami Borzadaran, G.R.
    • Communications for Statistical Applications and Methods
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    • v.22 no.2
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    • pp.105-120
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    • 2015
  • A large family of distributions arising from distributions of ordered data is proposed which contains other models studied in the literature. This extension subsume many cases of weighted random variables such as order statistics, records, k-records and many others in variety. Such a distribution can be used for modeling data which are not identical in distribution. Some properties of the theoretical model such as moment, mean deviation, entropy criteria, symmetry and unimodality are derived. The proposed model also studies the problem of parameter estimation and derives maximum likelihood estimators in a weighted gamma distribution. Finally, it will be shown that the proposed model is the best among the previously introduced distributions for modeling a real data set.