• Title/Summary/Keyword: independent random variables

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An approximate maximum likelihood estimator in a weighted exponential distribution

  • Lee, Jang-Choon;Lee, Chang-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.1
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    • pp.219-225
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    • 2012
  • We derive approximate maximum likelihood estimators of two parameters in a weighted exponential distribution, and derive the density function for the ratio Y=(X+Y) of two independent weighted exponential random variables X and Y, and then observe the skewness of the ratio density.

GENERALIZED CONVOLUTION OF UNIFORM DISTRIBUTIONS

  • Kang, Jong-Seong;Kim, Sung-Lai;Kim, Yang-Hee;Jang, Yu-Seon
    • Journal of applied mathematics & informatics
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    • v.28 no.5_6
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    • pp.1573-1581
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    • 2010
  • we investigate the n-fold convolution of the uniform distributions. First, we are concerned with the explicit distribution function of the partial sum ${\zeta}_n$ when the random variables are independent and has identically uniform distribution, next, we determine the n-fold convolution distribution of ${\zeta}_n$ when the identically distributed condition is not satisfied.

THE MINIMUM VARIANCE UNBIASED ESTIMATION OF SYSTEM RELIABILITY

  • Park, C.J.;Kim, Jae-Joo
    • Journal of Korean Institute of Industrial Engineers
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    • v.4 no.1
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    • pp.29-32
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    • 1978
  • We obtain the minimum variance unbiased estimate of system reliability when a system consists of n components whose life times are assumed to be independent and identically distributed either negative exponential or geometric random variables. For the case of a negative exponential life time, we obtain the minimum variance unbiased estimate of the probability density function of the i-th order statistic.

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Asymptotic Distribution of Sample Autocorrelation Function for the First-order Bilinear Time Series Model

  • Kim, Won-Kyung
    • Journal of the Korean Statistical Society
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    • v.19 no.2
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    • pp.139-144
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    • 1990
  • For the first-order bilinear time series model $X_t = aX_{t-1} + e_i + be_{t-1}X_{t-1}$ where ${e_i}$ is a sequence of independent normal random variables with mean 0 and variance $\sigma^2$, the asymptotic distribution of sample autocarrelation function is obtained and shown to follow a normal distribution. The variance of the asymptotic distribution is of a complicated form and hence a bootstrap estimate of the variance is proposed for large sample inference. This result can be used to distinguish between different bilinear models.

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A NOTE ON LATTICE DISTRIBUTIONS ON THE TORUS

  • Park, Chong-Jin;Lee, Kyu-Seok
    • Journal of the Korean Statistical Society
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    • v.32 no.1
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    • pp.21-24
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    • 2003
  • In the recent papers by Harris and Park (1994) and by Hui and Park (2000), a family of lattice distributions derived from a sum of independent identically distributed random variables is examined. In this paper we generalize a result of Hui and Park (2000) on lattice distributions on the torus using the Poisson summation formula.

Pattern Recognition and It's Computer Program(By Canonical Discriminant Analysis) (분류방법과 그의 전산화에 관한 연구 - 정준판별분석법을 중심으로 -)

  • Kim, Jae-Ju;Kim, Seong-Ju
    • Journal of Korean Society for Quality Management
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    • v.8 no.1
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    • pp.8-15
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    • 1980
  • There are many methods of pattern recognition. In this paper we assume that the responses of independent m groups are described by p-variate normal random variables with distinct mean vectors and a common covariance matrix. Under the assumption we give pattern recognition of m groups by means of canonical discrininant analysis and it's computer program. An example is presented.

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Machine Quality Assurance and TPM in FA System (FA 시스템에서의 품질보전과 TPM)

  • 유정상;황의철
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.15 no.25
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    • pp.75-82
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    • 1992
  • Standard acceptance sampling plans models the production pricess as a sequence of independent identically distributed Beruoulli random variables. However, the quality of items sampled sequentially from an ongoing production process of ten exhibits statistical dependency that is not accounted for in standard acceptance sampling plans. In this paper, a dependent production process is modelled as an ARMA process and as a two-state Markov chain. A simulation study of each is performed. A comparison of the probability of acceptance is done for the simulation method and for the approximation method.

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CHARACTERIZATION OF STANDARD EXTREME VALUE DISTRIBUTIONS USING RECORDS

  • Skrivankova, Valeria;Juhas, Matej
    • Journal of the Chungcheong Mathematical Society
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    • v.24 no.3
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    • pp.401-407
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    • 2011
  • The paper deals with characterization of standard Gumbel distribution and standard $Fr{\acute{e}}chet$ distribution and was motivated by [4], where the Weibull distribution is characterized. We present criterions using the independence of some suitable functions of lower records in a sequence of independent identically distributed random variables $\{X_n,\;n{\geq}1\}$.