• 제목/요약/키워드: limiting distribution

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A Simple Nonparametric Test of Complete Independence

  • Park, Cheol-Yong
    • Communications for Statistical Applications and Methods
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    • 제5권2호
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    • pp.411-416
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    • 1998
  • A simple nonparametric test of complete or total independence is suggested for continuous multivariate distributions. This procedure first discretizes the original variables based on their order statistics, and then tests the hypothesis of complete independence for the resulting contingency table. Under the hypothesis of independence, the chi-squared test statistic has an asymptotic chi-squared distribution. We present a simulation study to illustrate the accuracy in finite samples of the limiting distribution of the test statistic. We compare our method to another nonparametric test of complete independence via a simulation study. Finally, we apply our method to the residuals from a real data set.

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Extreme Value of Moving Average Processes with Negative Binomial Noise Distribution

  • Park, You-Sung
    • Journal of the Korean Statistical Society
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    • 제21권2호
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    • pp.167-177
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    • 1992
  • In this paper, we investigate the limiting distribution of $M_n = max (X_1, X-2, \cdots, X_n)$ in the infinite moving average process ${X_t = \sum c_i Z_{t-i}}$ generated from i.i.d. negative binomial variables $Z_i$'s. While no limit result is possible, nonetheless asymptotic bounds are derived. We also present the tail behavior of $X_t$, i.e., weighted sum of i.i.d. random variables. This continues a study made by Rootzen (1986) for discrete innovation sequences.

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A SINGLE SERVER RETRIAL QUEUE WITH VACATION

  • Kalyanaraman, R.;Murugan, S. Pazhani Bala
    • Journal of applied mathematics & informatics
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    • 제26권3_4호
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    • pp.721-732
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    • 2008
  • A single server infinite capacity queueing system with Poisson arrival and a general service time distribution along with repeated attempt and server vacation is considered. We made a comprehensive analysis of the system including ergodicity and limiting behaviour. Some operating characteristics are derived and numerical results are presented to test the feasibility of the queueing model.

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SOME LIMIT THEOREMS FOR POSITIVE RECURRENT AGE-DEPENDENT BRANCHING PROCESSES

  • Kang, Hye-Jeong
    • 대한수학회지
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    • 제38권1호
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    • pp.25-35
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    • 2001
  • In this paper we consider an age dependent branching process whose particles move according to a Markov process with continuous state space. The Markov process is assumed to the stationary with independent increments and positive recurrent. We find some sufficient conditions for he Markov motion process such that the empirical distribution of the positions converges to the limiting distribution of the motion process.

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A Bayesian Approach to Finite Population Sampling Using the Concept of Pivotal Quantity

  • Hwang, Hyungtae
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.647-654
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    • 2003
  • Bayesian probability models for finite populations are considered assuming so-called the super-population. We find the posterior distribution of population mean by a new approach, using the concept of pivotal quantity for the small sample case. A large sample theory is also treated throught the concept of asymptotically pivotal quantity.

Joint distribution of ESACF arrays within triangular zero boundary

  • Park, Sung-Joo;Jeon, Tae-Joon
    • 한국경영과학회지
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    • 제10권2호
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    • pp.28-37
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    • 1985
  • An obvious of ESACF approach for model identification by Tsay and Tiao(1984) is that the user may be confused by the elements which are in triangular but marginally larger two standard deviation values. To avoid this drawback, the joint limiting distribution of the vector whose elements are in triangular of ESACF arrays is verified and the statistics to test the nulity of the vector suggested. We illustrate this approach with three examples.

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A Unit Root Test Based on Bootstrapping

  • Shin, Key-Il;Kang, Hee-Jeong
    • Communications for Statistical Applications and Methods
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    • 제3권1호
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    • pp.257-265
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    • 1996
  • We consider nonstationary autoregressive autoregressive process with infinite variance of error. In the case of infinite cariance, the limiting distribution of the estimated coefficient is different from that under the finite cariance assumption. In this paper we show that the bootstrap method can be used to approximate the distribution of ordinary least squares estimator of the coefficient in the first order random walk process with infinite variance through some empirical studies and we suggest a test procedure based on bootstrap method for the unit root test.

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The Nonparametric Test for Detecting Main Effects for Three-Way ANOVA Models

  • Park, Young-Hun
    • Journal of the Korean Statistical Society
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    • 제25권3호
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    • pp.419-432
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    • 1996
  • When interactions are not present in a three-way layout, the lim-iting null distribution of the F statistic for testing main effects when applied to the rank-score transformed data is the same as the limiting null distribution of the usual F statistic when applied to the normal data. The simulation results exhibit that the rank transform test is robust with respect to significance level and powerful for testing main effects in a three-way factorial experiment.

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The Chi-squared Test of Independence for a Multi-way Contingency Table wish All Margins Fixed

  • Park, Cheolyong
    • Journal of the Korean Statistical Society
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    • 제27권2호
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    • pp.197-203
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    • 1998
  • To test the hypothesis of complete or total independence for a multi-way contingency table, the Pearson chi-squared test statistic is usually employed under Poisson or multinomial models. It is well known that, under the hypothesis, this statistic follows an asymptotic chi-squared distribution. We consider the case where all marginal sums of the contingency table are fixed. Using conditional limit theorems, we show that the chi-squared test statistic has the same limiting distribution for this case.

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혼합 얼랑 확률변수의 극한치 (Extreme Values of Mixed Erlang Random Variables)

  • Kang, Sung-Yeol
    • 한국경영과학회지
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    • 제28권4호
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    • pp.145-153
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    • 2003
  • In this Paper, we examine the limiting distributional behaviour of extreme values of mixed Erlang random variables. We show that, in the finite mixture of Erlang distributions, the component distribution with an asymptotically dominant tail has a critical effect on the asymptotic extreme behavior of the mixture distribution and it converges to the Gumbel extreme-value distribution. Normalizing constants are also established. We apply this result to characterize the asymptotic distribution of maxima of sojourn times in M/M/s queuing system. We also show that Erlang mixtures with continuous mixing may converge to the Gumbel or Type II extreme-value distribution depending on their mixing distributions, considering two special cases of uniform mixing and exponential mixing.