• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.15-27
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• 2018

Parametric method of flood frequency analysis involves fitting of a probability distribution to observed flood data. When record length at a given site is relatively shorter and hard to apply the asymptotic theory, an alternative distribution to the generalized extreme value (GEV) distribution is often used. In this study, we consider the beta-P distribution (BPD) as an alternative to the GEV and other well-known distributions for modeling extreme events of small or moderate samples as well as highly skewed or heavy tailed data. The L-moments ratio diagram shows that special cases of the BPD include the generalized logistic, three-parameter log-normal, and GEV distributions. To estimate the parameters in the distribution, the method of moments, L-moments, and maximum likelihood estimation methods are considered. A Monte-Carlo study is then conducted to compare these three estimation methods. Our result suggests that the L-moments estimator works better than the other estimators for this model of small or moderate samples. Two applications to the annual maximum stream flow of Colorado and the rainfall data from cloud seeding experiments in Southern Florida are reported to show the usefulness of the BPD for modeling hydrologic events. In these examples, BPD turns out to work better than $beta-{\kappa}$, Gumbel, and GEV distributions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.3
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• pp.75-83
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• 1984

The probability of failure is used to analyze the reliability of three dimensional slope failure, instead of conventional factor of safety. The strength parameters are assumed to be normal variated and beta variated. These are interval estimated under the specified confidence level and maximum likelihood estimation. The pseudonormal and beta random variables are generated using the uniform probability transformation method according to central limit theorem and rejection method. By means of a Monte-Carlo Simulation, the probability of failure is defined as; $P_f=M/N$ N: Total number of trials M: Total number of failures Some of the conclusions derived. from the case study include; 1. Three dimensional factors of safety are generally much higher than 2-D factors of safety. However situations appear to exist where the 3-D factor of safety can be lower than the 2-D factor of safety. 2. The $F_3/F_2$ ratio appears to be quite sensitive to c and ${\phi}$ and to the shape of the 3-D shear surface and the slope but not to be to the unit weight of soil. 3. From the two models (normal, beta) considered for the distribution of the factor of safety, the beta distribution generally provides lager than normal distribution. 4. Results obtained using the beta and normal models are presented in a nomgraph relating slope height and slop angle to probability of failure.

• IE interfaces
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• v.22 no.3
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• pp.214-222
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• 2009

In the early design stage, system reliability must be estimated from life testing data at the component level. Previously, a point estimate of system reliability was obtained from the unbiased estimate of the component reliability after assuming that the number of failed components for a given time followed a binomial distribution. For deriving the confidence interval of system reliability, either the lognormal distribution or the normal approximation of the binomial distribution was assumed for the estimator of system reliability. In this paper, a new estimator is used for the component level reliability, which is biased but has a smaller mean square error than the previous one. We propose to use the beta distribution rather than the lognormal or approximated normal distribution for developing the confidence interval of the system reliability. A numerical example based on Monte Carlo simulation illustrates advantages of the proposed approach over the previous approach.

• Journal of the Korean Statistical Society
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• v.26 no.1
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• pp.1-22
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• 1997

In the linear regression model $y_{i}$ = .alpha. $x_{i}$ $^{T}$ .beta. + .epsilon.$_{i}$ , i = 1,2,...,n, the weighted pairwise absolute deviation (WPAD) estimator was defined by minimizing the dispersion function D (.beta.) = .sum..sum.$_{{i $w_{{ij}}$$\mid$ $r_{j}$ (.beta.) $r_{i}$ (.beta.)$\mid$, where $r_{i}$ (.beta.)'s are residuals and $w_{{ij}}$'s are weights. This estimator can achive bounded total influence with positive breakdown by choice of weights $w_{{ij}}$. In this paper, we consider a more general type of dispersion function than that of D(.beta.) and propose a pairwise GM-estimator based on the dispersion function. Under some regularity conditions, the proposed estimator has a bounded influence function, a high breakdown point, and asymptotically a normal distribution. Results of a small-sample Monte Carlo study are also presented. presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.69-79
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• 1999

The main objective of this study are to propose two methods that would be a comprehensive measure of evaluation for non-normal process capability with Beta distributions. First method is introduced using process capability index $C_{psk}$ by the Pearson system and Johnson system. The Pearson system and the Johnson System selected for process capability index calculation have a equivalent result of this study that the ranking of the seven indices in terms of sensitivity to departure of the process median from the target value from the most sensitive one up to the least sensitive are $C^{*}_{pm}$ , $C_{psk}$ , $C_{s}$ , $C_{pmk}$ , $C_{pm}$ , $C_{pk}$ , $C_{p}$ . Second method show using the percentage nonconforming by the Pearson, Johnson and Burr functions. In thus study, we find that the Pearson system and the Burr system are a reasonable method to estimate percentage nonconforming. But, the exact procedure for deriving this estimate will be based on Beta distribution. Accordingly, if a process is not normally distributed , but normal-based techniques are used serious errors can result.

• Archives of Pharmacal Research
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• v.22 no.1
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• pp.1-8
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• 1999

Transforming growth factor-$\beta$ (TGF-$\beta$) is the prototypical multifunctional cytokine, participating in the regulation of vital cellular activities such as proliferation and differentiations as well as a number of basic physiological functions. The effects of TGF-$\beta$ are critically dependent on the expression and distribution of a family of TGF-$\beta$ receptors, the TGF-$\beta$ types I, II, and III. It is now known that a wide variety of human pathology can be caused by aberrant expression and function of these receptors. the coding sequence of the type II receptor (RII) appears to render it uniquely susceptible to DNA replication errors in the course of normal cell division. By virtue of its key role in the regulation of cell proliferation, TGF-$\beta$ RII should be considered as a tumor suppressor gene. High levels of mutation in the TGF-$\beta$ RII gene have been observed in a wide range of primarily epithelial malignancies, including colon and gastric cancer. It appears likely that mutation of the TGF-$\beta$ RII gene may be a very critical step in the pathway of carcinogenesis.

• Journal of the Korean Professional Engineers Association
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• v.21 no.4
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• pp.19-32
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• 1988

Whereas is non-symmetrical distribution manufacturing process the traditional X-chart by Shewhart is not plotted relatively on the central line but plotted on the skew of upper-hand side or lower-hand side. That is to say, for the purpose of producing either upper-specification-oriented items or lower-specification-oriented items, and when we carry out tighter control so as to have them pass only its specifications, the distribution shape naturally has a non-normal distribution. In the Shewhart X-chart, which is the most widely used one in Korea, such skewed distributions make tile plots to be inclined below or above the central line or outside the control limits although no assignable causes can be found. To overcome such short comings is non-normally distributed processes, a distribution-free type of confidence interval can be used, which should be haled on order statistics. This thesis is concerned with the design of control chart based on a sample median which is easy to use in practical situation and therefore properties for non-normal distributions, such as Gamma, Beta, Lognormal, Weibull, Pareto, and Truncated-normal distributions, may be easily analyzed. To enhance this improvement, I proved the property of practical applications of control chart method by comparing and analyzing the case studies of practical application of special purpose control chart method, and also by introducing the new designed median control chart.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.12
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• pp.1684-1690
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• 2014

Estrogen and its receptors are essential hormones for normal reproductive function in males and females during developmental stage. To better understand the effect of estrogen receptor (ER) gene in yak (Bos grunniens), reverse transcription-polymerase chain reaction (PCR) was carried out to clone $ER{\alpha}$ and $ER{\beta}$ genes. Bioinformatics methods were used to analyze the evolutionary relationship between yaks and other species, and real-time PCR was performed to identify the mRNA expression of $ER{\alpha}$ and $ER{\beta}$. Sequence analysis showed that the ER open reading frames (ORFs) encoded 596 and 527 amino acid proteins. The yak $ER{\alpha}$ and $ER{\beta}$ shared 45.3% to 99.5% and 53.9% to 99.1% protein sequence identities with other species homologs, respectively. Real-time PCR analysis revealed that $ER{\alpha}$ and $ER{\beta}$ were expressed in a variety of tissues, but the expression level of $ER{\alpha}$ was higher than that of $ER{\beta}$ in all tissues, except testis. The mRNA expression of $ER{\alpha}$ was highest in the mammary gland, followed by uterus, oviduct, and ovary, and lowest in the liver, kidney, lung, testis, spleen, and heart. The $ER{\beta}$ mRNA level was highest in the ovary; intermediary in the uterus and oviduct; and lowest in the heart, liver, spleen, lung, kidney, mammary gland, and testis. The identification and tissue distribution of ER genes in yaks provides a foundation for the further study on their biological functions.

• Journal for History of Mathematics
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• v.13 no.1
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• pp.1-14
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• 2000

The first part of this thesis discusses the Pearson's Curve Family which gives $\beta$distribution, $\Gamma$-distribution, $X^2$-distribution and t-distribution. The second part of this thesis gives some brief process of calculations for normal distribution density and t-distribution density by the 7-th type Curve of Pearson's Curve Family. Finally, a conclusion arrives that Student(Gosset) could not find out his famous 'Student's t-distribution' without his attending of 'Pearson's Differential Equation' class taught by Pearson himself when he was a senior student. However, if he had got a professorship at the Pearson Statistics Laboratory, the University of London, then he could not have found 'Student's t-distribution' for small sampling technique of modern statistics.

• The Mathematical Education
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• v.41 no.1
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• pp.109-126
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• 2002

In this thesis. we estimated the good reliability coefficient ${\beta}$$\sub$k/ that is unbiased, consistent and more efficient than Cronbach's ${\alpha}$$\sub$k/ in splitting of a test into several formats of subtests and several properties of ${\beta}$$\sub$k/ are also represented. The tables of coefficients of skewness and kurtosis are represented to test the significance of departures from normality. We got the cumulative normal plots of z'from the distribution which is departed from normality using the Bock's approximation procedure and we finally enumerated the transformed standardized scores z'and a new raw score X' which enable us to proceed further evaluation procedures depending on our assessment policy.