• 제목/요약/키워드: Rank Functions

검색결과 115건 처리시간 0.025초

불완전계수의 선형모형에서 추정가능함수 (Estimable functions of less than full rank linear model)

  • 최재성
    • Journal of the Korean Data and Information Science Society
    • /
    • 제24권2호
    • /
    • pp.333-339
    • /
    • 2013
  • 본 논문은 불완전계수의 모형행렬을 갖는 선형모형에서 추정가능함수를 다루고 있다. 고정효과 모형의 모수들은 일반적으로 추정가능한 모수가 아니므로 추정가능한 모수들의 함수를 구하기 위한 방법으로 완전계수의 인자분해 방법을 제시하고 있다. 완전계수의 인자분해 방법으로 구해진 추정가능함수의 타당성을 확인하기 위한 사영행렬은 불완전계수의 모형행렬을 구성하는 행벡터로 생성되는 벡터공간으로의 사영행렬과 동일함을 보여주고 있다. 완전계수의 인자분해로 추정가능함수를 구하는 방법과 모수들의 선형함수가 추정가능함수인 가의 확인을 위한 사영행렬의 이용에 관해 벡터공간의 관점에서 다루어지고 있다. 또한, 추정가능함수의 기저 구성에 관한 구체적 논의가 행해지고 있다.

국소 최적 순위 검파기의 점수 함수의 합과 가중합 (Sums and Weighted Sums of the Score functions of Locally Optimum Rank Detectors)

  • 배진수;박현경;송익호
    • 한국통신학회논문지
    • /
    • 제27권6A호
    • /
    • pp.517-523
    • /
    • 2002
  • 이 논문에서는 국소 최적 순위 검파기의 점수 함수의 합과 가중합의 완전한 골을 유도하였다. 순위통계량과 부호통계량에 바탕을 둔 검파기의 점근 성능 특성은 점수 함수의 합과 가 중합으로부터 얻어지기 때문에, 합과 가중합은 매우 중요하나, 이들을 구하기 위해서는 상당한 수학적 조작이 필요하다. 이 논문에서 다루어진 점수 함수는 순위통계량에 바탕을 둔 것들 뿐 아니라 절대값 순위통계량과 부호통계량에 바탕을 둔 것들을 포함한다. 따라서, 이 논문의 결과를 써서 여러 가지 잡음 모형에서 쓸모 있는 검 파기들의 점근 성능을 쉽게 구할 수 있다.

An Orthogonal Representation of Estimable Functions

  • Yi, Seong-Baek
    • Communications for Statistical Applications and Methods
    • /
    • 제15권6호
    • /
    • pp.837-842
    • /
    • 2008
  • Students taking linear model courses have difficulty in determining which parametric functions are estimable when the design matrix of a linear model is rank deficient. In this note a special form of estimable functions is presented with a linear combination of some orthogonal estimable functions. Here, the orthogonality means the least squares estimators of the estimable functions are uncorrelated and have the same variance. The number of the orthogonal estimable functions composing the special form is equal to the rank of the design matrix. The orthogonal estimable functions can be easily obtained through the singular value decomposition of the design matrix.

Analysing the Combined Kerberos Timed Authentication Protocol and Frequent Key Renewal Using CSP and Rank Functions

  • Kirsal-Ever, Yoney;Eneh, Agozie;Gemikonakli, Orhan;Mostarda, Leonardo
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제8권12호
    • /
    • pp.4604-4623
    • /
    • 2014
  • Authentication mechanisms coupled with strong encryption techniques are used for network security purposes; however, given sufficient time, well-equipped intruders are successful for compromising system security. The authentication protocols often fail when they are analysed critically. Formal approaches have emerged to analyse protocol failures. In this study, Communicating Sequential Processes (CSP) which is an abstract language designed especially for the description of communication patterns is employed. Rank functions are also used for verification and analysis which are helpful to establish that some critical information is not available to the intruder. In order to establish this, by assigning a value or rank to each critical information, it is shown that all the critical information that can be generated within the network have a particular characterizing property. This paper presents an application of rank functions approach to an authentication protocol that combines delaying the decryption process with timed authentication while keys are dynamically renewed under pseudo-secure situations. The analysis and verification of authentication properties and results are presented and discussed.

Test Statistics for Volume under the ROC Surface and Hypervolume under the ROC Manifold

  • Hong, Chong Sun;Cho, Min Ho
    • Communications for Statistical Applications and Methods
    • /
    • 제22권4호
    • /
    • pp.377-387
    • /
    • 2015
  • The area under the ROC curve can be represented by both Mann-Whitney and Wilcoxon rank sum statistics. Consider an ROC surface and manifold equal to three dimensions or more. This paper finds that the volume under the ROC surface (VUS) and the hypervolume under the ROC manifold (HUM) could be derived as functions of both conditional Mann-Whitney statistics and conditional Wilcoxon rank sum statistics. The nullhypothesis equal to three distribution functions or more are identical can be tested using VUS and HUM statistics based on the asymptotic large sample theory of Wilcoxon rank sum statistics. Illustrative examples with three and four random samples show that two approaches give the same VUS and $HUM^4$. The equivalence of several distribution functions is also tested with VUS and $HUM^4$ in terms of conditional Wilcoxon rank sum statistics.

A Method of Obtaning Least Squares Estimators of Estimable Functions in Classification Linear Models

  • Kim, Byung-Hwee;Chang, In-Hong;Dong, Kyung-Hwa
    • Journal of the Korean Statistical Society
    • /
    • 제28권2호
    • /
    • pp.183-193
    • /
    • 1999
  • In the problem of estimating estimable functions in classification linear models, we propose a method of obtaining least squares estimators of estimable functions. This method is based on the hierarchical Bayesian approach for estimating a vector of unknown parameters. Also, we verify that estimators obtained by our method are identical to least squares estimators of estimable functions obtained by using either generalized inverses or full rank reparametrization of the models. Some examples are given which illustrate our results.

  • PDF

Variable Selection with Nonconcave Penalty Function on Reduced-Rank Regression

  • Jung, Sang Yong;Park, Chongsun
    • Communications for Statistical Applications and Methods
    • /
    • 제22권1호
    • /
    • pp.41-54
    • /
    • 2015
  • In this article, we propose nonconcave penalties on a reduced-rank regression model to select variables and estimate coefficients simultaneously. We apply HARD (hard thresholding) and SCAD (smoothly clipped absolute deviation) symmetric penalty functions with singularities at the origin, and bounded by a constant to reduce bias. In our simulation study and real data analysis, the new method is compared with an existing variable selection method using $L_1$ penalty that exhibits competitive performance in prediction and variable selection. Instead of using only one type of penalty function, we use two or three penalty functions simultaneously and take advantages of various types of penalty functions together to select relevant predictors and estimation to improve the overall performance of model fitting.

위치모수 변화 모형에서 순위함수와 평균함수를 이용한 비모수적 변화점 추정 (Nonparametric Change-point Estimation with Rank and Mean Functions in a Location Parameter Change Model)

  • 김재희;이경원
    • Journal of the Korean Data and Information Science Society
    • /
    • 제11권2호
    • /
    • pp.279-293
    • /
    • 2000
  • 위치 모수에 대해 1개의 변화점이 있는 경우 Carlstein(1988)의 변화점 추정량을 순위함수와 평균함수를 이용하여 변형시킨 변화점 추정통계량을 제안하였다. 모의 실험을 통해 Carlstein(1988) 변화점 추정량과 제안하는 변화점 추정량의 평균, 평균제곱오차와 변화점 추정비율을 계산하여 비교하였다.

  • PDF