• Title/Summary/Keyword: Statistical distributions

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Parametric Tests and Estimation of Mean Change in Discrete Distributions

  • Kim, Jae-Hee;Cheon, Soo-Young
    • Communications for Statistical Applications and Methods
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    • v.16 no.3
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    • pp.511-518
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    • 2009
  • We consider the problem of testing for change and estimating the unknown change-point in a sequence of time-ordered observations from the binomial and Poisson distributions. Including the likelihood ratio test, Gombay and Horvath (1990) tests are studied and the proposed change-point estimator is derived from their test statistic. A power study of tests and a comparison study of change-point estimators are done via simulation.

Analysis on the Amino Acid Distributions with Position in Transmembrane Proteins

  • Chi, Sang-Mun
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.745-758
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    • 2005
  • This paper presents a statistical analysis on the position-specific distributions of amino acid residues in transmembrane proteins. A hidden Markov model segments membrane proteins to produce segmented regions of homogeneous statistical property from variable-length amino acids sequences. These segmented residues are analyzed by using chi-square statistic and relative-entropy in order to find position-specific amino acids. This analysis showed that isoleucine and valine concentrated on the center of membrane-spanning regions, tryptophan, tyrosine and positive residues were found frequently near both ends of membrane.

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Empirical Bayes Estimation of the Binomial and Normal Parameters

  • Hong, Jee-Chang;Inha Jung
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.87-96
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    • 2001
  • We consider the empirical Bayes estimation problems with the binomial and normal components when the prior distributions are unknown but are assumed to be in certain families. There may be the families of all distributions on the parameter space or subfamilies such as the parametric families of conjugate priors. We treat both cases and establish the asymptotic optimality for the corresponding decision procedures.

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New Dispersion Function in the Rank Regression

  • Choi, Young-Hun
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.101-113
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    • 2002
  • In this paper we introduce a new score generating (unction for the rank regression in the linear regression model. The score function compares the $\gamma$'th and s\`th power of the tail probabilities of the underlying probability distribution. We show that the rank estimate asymptotically converges to a multivariate normal. further we derive the asymptotic Pitman relative efficiencies and the most efficient values of $\gamma$ and s under the symmetric distribution such as uniform, normal, cauchy and double exponential distributions and the asymmetric distribution such as exponential and lognormal distributions respectively.

Nonparametric Test for Multivariate Location Translation Alternatives

  • Na, Jong-Hwa
    • Communications for Statistical Applications and Methods
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    • v.7 no.3
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    • pp.799-809
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    • 2000
  • In this paper we propose a nonparametric one sided test for location parameters in p-variate(p$\geq$2) location translation model. The exact null distributions of test statistics are calculated by permutation principle in the case of relatively small sample sizes and the asymptotic distributions are also considered. The powers of various tests are compared through computer simulation and thep-values with real data are also suggested through example.

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Moments of a Class of Internally Truncated Normal Distributions

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.679-686
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    • 2007
  • Moment expressions are derived for the internally truncated normal distributions commonly applied to screening and constrained problems. They are obtained from using a recursive relation between the moments of the normal distribution whose distribution is truncated in its internal part. Closed form formulae for the moments can be presented up to $N^{th}$ order under the internally truncated case. Necessary theories and two applications are provided.

Kullback-Leibler Information in View of an Extended Version of κ-Records

  • Ahmadi, Mosayeba;Mohtashami Borzadaran, G.R.
    • Communications for Statistical Applications and Methods
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    • v.20 no.1
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    • pp.1-13
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    • 2013
  • This paper introduces an extended version of ${\kappa}$-records. Kullback-Leibler (K-L) information between two generalized distributions arising from ${\kappa}$-records is derived; subsequently, it is shown that K-L information does not depend on the baseline distribution. The behavior of K-L information for order statistics and ${\kappa}$-records, is studied. The exact expressions for K-L information between distributions of order statistics and upper (lower) ${\kappa}$-records are obtained and some special cases are provided.

On Characterizing Distributions by Some Properties of the Distribution Truncated at the rth order Statistic

  • Sangun Park
    • Communications for Statistical Applications and Methods
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    • v.1 no.1
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    • pp.52-56
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    • 1994
  • When we have an i.i.d. sample of size n from a continuous distribution, the distribution truncated on the left at the rth order statistic plays an important role in the theoretical analysis of the Type 2 censored data. The charaterization of distributions by the average of the conditional expectation and the average of the conditional information concerning the truncated distribution is studied here.

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A SKEWED GENERALIZED t DISTRIBUTION

  • NADARAJAH SARALEES
    • Journal of the Korean Statistical Society
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    • v.34 no.4
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    • pp.311-329
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    • 2005
  • Skewed t distributions have attracted significant attention in the last few years. In this paper, a generalization - referred to as the skewed generalized t distribution - with the pdf f(x) = 2g(x)G(${\lambda}x$) is introduced, where g(${\cdot}$) and G (${\cdot}$) are taken, respectively, to be the pdf and the cdf of the generalized t distribution due to McDonald and Newey (1984, 1988). Several particular cases of this distribution are identified and various representations for its moments derived. An application is provided to rainfall data from Orlando, Florida.

Bayesian Estimation for Skew Normal Distributions Using Data Augmentation

  • Kim Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.323-333
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    • 2005
  • In this paper, we develop a MCMC method for estimating the skew normal distributions. The method utilizing the data augmentation technique gives a simple way of inferring the distribution where fully parametric frequentist approaches are not available for small to moderate sample cases. Necessary theories involved in the method and computation are provided. Two numerical examples are given to demonstrate the performance of the method.