• Honam Mathematical Journal
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• v.25 no.1
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• pp.95-115
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• 2003

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p{\geq}4)$ under the quadratic loss, based on a sample $X_1,\;{\cdots}X_n$. We find an optimal decision rule within the class of Lindley type decision rules which shrink the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $||{\theta}-{\bar{\theta}}1||$ is known, where ${\bar{\theta}}=(1/p)\sum_{i=1}^p{\theta}_i$ and 1 is the column vector of ones. When the norm is restricted to a known interval, typically no optimal Lindley type rule exists but we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1027-1039
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• 2005

Consider the problem of estimating a $p{\times}1$ mean vector $\theta(p\geq4)$ under the quadratic loss, based on a sample $X_1$, $X_2$, $\cdots$, $X_n$. We find a Lindley type decision rule which shrinks the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $\parallel\;{\theta}-\bar{{\theta}}1\;{\parallel}$ is restricted to a known interval, where $bar{{\theta}}=\frac{1}{p}\;\sum\limits_{i=1}^{p}{\theta}_i$ and 1 is the column vector of ones. In this case, we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.

• Journal of Integrative Natural Science
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• v.10 no.1
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• pp.33-39
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• 2017

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p-q{\geq}3)$, $q=rank(P_V)$ with a projection matrix $P_v$ under the quadratic loss, based on a sample $X_1$, $X_2$, ${\cdots}$, $X_n$. We find a James-Stein type decision rule which shrinks towards projection vector when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}{\theta}-P_V{\theta}{\parallel}$ is restricted to a known interval, where $P_V$ is an idempotent and projection matrix and rank $(P_V)=q$. In this case, we characterize a minimal complete class within the class of James-Stein type decision rules. We also characterize the subclass of James-Stein type decision rules that dominate the sample mean.

• Journal of Veterinary Science
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• v.23 no.6
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• pp.70.1-70.13
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• 2022

Background: Fat stranding is a non-specific finding of an increased fat attenuation on computed tomography (CT) images. Fat stranding is used for detecting the underlying lesion in humans. Objectives: To assess the clinical significance of fat stranding on CT images for identifying the underlying cause in dogs and cats. Methods: In this retrospective study, the incidence, location, extent, distribution, and pattern of fat stranding were assessed on CT studies obtained from 134 cases. Results: Fat stranding was found in 38% (51/134) of all cases and in 35% (37/107) of tumors, which was significantly higher in malignant tumors (44%) than benign tumors (12%). Moreover, fat stranding was found in more than two areas in malignant tumors (16/33) and in a single area in benign tumors (4/4). In inflammation, fat stranding was demonstrated in 54% (7/13) in a single area (7/7) as a focal distribution (6/7). In trauma, fat stranding was revealed in 50% (7/14) and most were in multiple areas (6/7). Regardless of the etiologies, fat stranding was always around the underlying lesion and a reticular pattern was the most common presentation. Logistic regression analysis revealed that multiple areas (p = 0.040) of fat stranding and a reticulonodular pattern (p = 0.022) are the significant predictors of malignant tumor. Conclusions: These findings indicated that CT fat stranding can be used as a clue for identifying the underlying lesion and can be useful for narrowing the differential list based on the extent and pattern.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.859-871
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• 2003

In this paper we introduce some adaptive M-estimators using selector statistics to estimate the slope of regression model under the symmetric and continuous underlying error distributions. This selector statistics is based on the residuals after the preliminary fit L$_1$ (least absolute estimator) and the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying symmetric distributions in the location model. If we use L$_1$ as a preliminary fit to get residuals, we find the asymptotic distribution of sample quantiles of residual are slightly different from that of sample quantiles in the location model. If we use the functions of sample quantiles of residuals as selector statistics, we find the suitable quantile points of residual based on maximizing the asymptotic distance index to discriminate distributions under consideration. In Monte Carlo study, this adaptive M-estimation method using selector statistics works pretty good in wide range of underlying error distributions.

• 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.

• Journal of Applied Reliability
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• v.3 no.2
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• pp.137-143
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• 2003

Sequential test plans are characterized by decision rules for accepting or rejecting compliance, or continuing the test at my test time. They are determined by selected values of risks and discrimination ratio. The sequential test plans in the international standard such as MIL-HDBK-781A are based on the assumption that the underlying distribution of times between failures is exponential. In this paper, sequential test plans are extended to the Weibull distribution case. Simulation studies are performed to examine the reasonability in this extension.

• International Journal of Highway Engineering
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• v.9 no.3
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• pp.135-143
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• 2007

The pavement system constructed by tieing a number of precast concrete slabs employing prestressing techniques is called the precast prestressed concrete pavement. The behavior of this type of pavement system under post-tensioning was analyzed using a finite element model. First, the optimal number of anchors was determined by investigating the distribution of compressive stresses in the pavement system due to post-tensioning. Then, the effects of the parameters such as the horizontal resistance of underlying layers, the pavement length, the slab thickness, and the bearing area of the anchorage on the distribution of compressive stresses were analyzed. The horizontal resistance of underlying layers induced the loss of compressive stresses, and the loss increased in the middle of the pavement. As the pavement length increased or the slab thickness decreased, the stress loss due to the horizontal resistance of underlying layers became larger. However, the bearing area of the anchorage where the compressive forces were applied did not much affect the distribution of compressive stresses.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.43.1-43.1
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• 2016

The duration of star formation activity is a key to understanding the formation process of star clusters. Although a number of astronomers have attempted to derive the underlying age spread in photometric diagrams with a variety of stellar evolutionary models, the resultant findings are subject to uncertainties due to intrinsic variability of pre-main sequence (PMS) stars, observational errors, difficulties in reddening correction, and systematic differences in adopted stellar evolutionary models. The distribution of Li abundance for PMS stars in a cluster could, on the other hand, provide an alternative way to estimate the age spread. In this study, a total of 134 PMS stars in NGC 2264 are observed with the high resolution multi-object spectrogragh Hectochelle attached to the 6.5m Multi Mirror Telescope. We have successfully detected Li ${\lambda}6708$ resonance doublet for 86 low-mass PMS stars. The Li abundance of the stars is derived from their equivalent width using a curves of growth method. After correction for non-LTE effects, the underlying age spread of 3 - 4 Myr is inferred from the Li abundance distribution of low-mass PMS stars. We suggest that NGC 2264 formed on a timescale shorter than 5 Myr given the presence of embedded populations.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.95-100
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• 2020

Nifty Bank Index has started trading in futures and options (F&O) segment from 13^th June 2005 in National Stock Exchange. The purpose of the study is to enhance the literature by examining expiration effect on the price volatility and price reversal of Underlying Index in India. Historical data used for the current study primarily comprise of daily close prices of Nifty Bank which is the only equity sectoral index in India which is traded in derivatives market and its Future contract value is derived from the underlying CNX Bank Index during the period 1^st January 2010 till 31^st March 2020. To check stationarity of the data, Augmented Dicky Fuller test was used. The study employed ARMA- EGARCH model for analysing the data. The empirical results revealed that there is no effect on the mean returns of underlying Index and EGARCH (1,1) model furthermore shows there is existence of leverage effect in the Bank Index i.e., negative shocks causes more fluctuations in the Index than positive news of similar magnitude. The outcome of the study specifies that there is no effect on volatility on the underlying sectoral index due to expiration days and also observed no price reversal effect once the expiration days are over.