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In this note, we make some comments about the paper of Alheety and Kibria (2014) and correct the wrongly proved Theorems in that paper. [ABSTRACT FROM AUTHOR]

In this paper, almost sure exponential stability and pth moment exponential stability of stochastic cellular neural networks with mixed delays are investigated. Employing the methods of stochastic analysis, the Lyapunov’s method, and useful inequality techniques, a sufficient condition ensuring the almost sure exponential stability and pth moment exponential stability is obtained. Two examples are given to illustrate this sufficient condition. [ABSTRACT FROM AUTHOR]

In this paper, we employ an intensity-based credit risk model with regime-switching to study the valuation of basket CDS in a homogeneous portfolio. We assume that the default intensities are described by some dependent regime-switching shot-noise processes and the individual jumps of the intensity are driven by a common factor. By using the conditional Laplace transform of the regime-switching shot-noise process, we obtain the closed form results for pricing the fair spreads of the basket CDS. We present some numerical examples to illustrate the effect of the model parameters on the fair spreads. [ABSTRACT FROM AUTHOR]

The proportional odds model gives a method of generating new family of distributions by adding a parameter, called tilt parameter, to expand an existing family of distributions. The new family of distributions so obtained is known as Marshall–Olkin family of distributions or Marshall–Olkin extended distributions. In this paper, we consider Marshall–Olkin family of distributions in discrete case with fixed tilt parameter. We study different ageing properties, as well as different stochastic orderings of this family of distributions. All the results of this paper are supported by several examples. [ABSTRACT FROM AUTHOR]

The present paper deals with the performance evaluation of an M / M / 1 retrial queue with collisions, transmission errors and unreliable server. To the best of our knowledge, there are no works that have dealt with retrial queues by considering all the above-mentioned aspects (collisions, transmission errors and unreliable server). This queue can be used as a mathematical model of several computer systems and telecommunication networks. We apply the generating function method to derive the joint distribution of the server state and the orbit length in the steady state, and we obtain some performance measures. Finally, we provide numerical illustrations to show the effectiveness and the applicability of the model. [ABSTRACT FROM AUTHOR]

In the present paper we develop bootstrap tests of hypothesis, based on simulation, for the transition probability matrix arising in the context of a multi-state model. The bootstrap test statistic is based on the paper of Tattar and Vaman (2008), which develops a statistic for the testing problems concerning the transition probability matrix of the non homogeneous Markov process. [ABSTRACT FROM PUBLISHER]

In this paper, the risk model with constant interest based on an entrance process is investigated. Under the assumptions that the entrance process is a renewal process and the claim sizes satisfy a certain dependency, which belong to the different heavy-tailed distribution classes, the finite-time and infinite-time asymptotic estimates of the risk model with constant interest force are obtained. [ABSTRACT FROM AUTHOR]

Let Xk, 1 ⩽ k ⩽ n, be n real-valued random variables, and θk, 1 ⩽ k ⩽ n, be another n non negative not-degenerate at zero random variables. Assume that random pairs (X1, θ1), …, (Xn, θn) are mutually independent, while each pair (Xk, θk) follows a wide type of dependence structure. Consider the randomly weighted sum Sθn = ∑k = 1nθkXk. In this paper, the tail asymptotics for Sθn in the case where Xk, 1 ⩽ k ⩽ n, belong to some heavy-tailed subclasses are firstly investigated. Then, as an application, we consider the tail behavior of the conditional tail expectation as q↑1, where . Under some technical conditions, the asymptotic estimate for the right tail of conditional tail expectation is also derived. The obtained results extend some existing ones in the literature. [ABSTRACT FROM AUTHOR]

Multilevel modeling is an important tool for analyzing large-scale assessment data. However, the standard multilevel modeling will typically give biased results for such complex survey data. This bias can be eliminated by introducing design weights which must be used carefully as they can affect the results. The aim of this paper is to examine different approaches and to give recommendations concerning handling design weights in multilevel models when analyzing large-scale assessments such as TIMSS (The Trends in International Mathematics and Science Study). To achieve the goal of the paper, we examined real data from two countries and included a simulation study. The analyses in the empirical study showed that using no weights or only level 1 weights sometimes could lead to misleading conclusions. The simulation study only showed small differences in estimation of the weighted and unweighted models when informative design weights were used. The use of unscaled or not rescaled weights however caused significant differences in some parameter estimates. [ABSTRACT FROM AUTHOR]

δ-shock model is one of the widely studied shock models in reliability. Under this model, the system fails when the time between two consecutive shocks falls below a fixed threshold δ. In this paper, the survival function and the mean time to failure of the system are obtained when the times between successive shocks follow proportional hazard rate model. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the precise large deviations for sums of not identical distributed random variables which are widely upper orthant dependent (WUOD, in short) and φ-mixing. The asymptotic relations for sums of random variables with dominated variation are obtained. [ABSTRACT FROM AUTHOR]

If the population size is not a multiple of the sample size, then the usual linear systematic sampling design is unattractive, since the sample size obtained will either vary, or be constant and different to the required sample size. Only a few modified systematic sampling designs are known to deal with this problem and in the presence of linear trend, most of these designs do not provide favorable results. In this paper, a modified systematic sampling design, known as remainder modified systematic sampling (RMSS), is introduced. There are seven cases of RMSS and the results in this paper suggest that the proposed design is favorable, regardless of each case, while providing linear trend-free sampling results for three of the seven cases. To obtain linear trend-free sampling for the other cases and thus improve results, an end corrections estimator is constructed. [ABSTRACT FROM AUTHOR]

In this paper, we consider a regression model and propose estimators which are the weighted averages of two estimators among three estimators; the Stein-rule (SR), the minimum mean squared error (MMSE), and the adjusted minimum mean-squared error (AMMSE) estimators. It is shown that one of the proposed estimators has smaller mean-squared error (MSE) than the positive-part Stein-rule (PSR) estimator over a moderate region of parameter space when the number of the regression coefficients is small (i.e., 3), and its MSE performance is comparable to the PSR estimator even when the number of the regression coefficients is not so small. [ABSTRACT FROM AUTHOR]

This paper deals with Monte Carlo simulation in case of dependent input random variables. We propose an algorithm to generate refined descriptive samples from dependent random variables for estimation of expectations of functions of output variables using the Iman and Conover algorithm to transform the dependent variables to independent ones. Therefore, such estimates obtained through a chosen mathematical model are compared with those obtained using the simple random sampling method, which proved that the former are the most efficient. Besides, using already published work on independent input variables, we can deduce in case of dependent input random variables, that asymptotically the variance of the RDS estimator is less than that of SRS estimator for any simulation function having finite second moment. [ABSTRACT FROM AUTHOR]

In this paper, we derive conditions under which second-order semi-Markov chains in state and duration admits a limit distribution. [ABSTRACT FROM AUTHOR]

The effect of heterogeneity on order statistics has attracted much attention in recent decades. In this paper, we study the skewness of extreme order statistics from heterogeneous samples in the scale models according to star ordering. It is shown that,without any restriction on the scale parameters, the skewness of extreme order statistics from heterogeneous samples is larger than that from homogeneous samples. We further extend this study to the multiple-outlier scale models. Some examples and applications are highlighted as well. [ABSTRACT FROM AUTHOR]

The paper considers a lognormal model for the survival times and obtains a Bayes solution by means of Gibbs sampler algorithm when the priors for the parameters are vague. The formulation given in the paper is mainly focused for censored data problems though it is equally well applicable for complete data scenarios as well. For the purpose of numerical illustration, we considered two real data sets on head and neck cancer patients when they have been treated using either radiotherapy or chemotherapy followed by radiotherapy. The paper not only compares the survival functions for the two therapies assuming a lognormal model but also provides a model compatibility study based on predictive simulation results so that the choice of lognormal model can be justified for the two data sets. The ease of our analysis as compared to an earlier approach is certainly an advantage. [ABSTRACT FROM PUBLISHER]

In this paper, we study the Gerber–Shiu (G-S) function for the classical risk model, in which the discount rate is generalized from a constant to a random variable. The discounted interest force accumulated process is modeled by a Poisson process and a Gaussian process for the G-S function. In terms of the standard techniques in ruin theory, we derive the integro-differential equation and the defective renewal equation satisfied by the G-S function. Then, the asymptotic formula for the G-S function is obtained using the renewal theory. [ABSTRACT FROM PUBLISHER]

In this paper, we first investigate some reliability properties in the proportional mean past lifetimes model. Specifically, some implications of stochastic orders and aging notions between random variables which have proportional mean past lifetimes are discussed. Then, as an extension, mixture model arising from the proportional mean past lifetimes model is introduced and preservation properties of some stochastic orders and aging notions concerning this mixture model are studied. We also study some negative dependence properties in the proposed mixture model. [ABSTRACT FROM PUBLISHER]

This paper studies the hedging problem of European contingent claims when the underlying asset is non traded. We assume that the share prices of the assets are governed by Markov-modulated processes; that is, the market parameters switch over the time according to a finite-state continuous time Markov chain. Due to the presence of Markov chain the non traded asset, the market which we consider is incomplete, we shall use the local risk minimization method to obtain an optimal hedging strategy in a closed-form for an investor. Finally, numerical illustrations of an optimal hedging strategy are given by the Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate how some results related to the complex normal distribution are relevant in size and shape analysis. Our main focus is on the derivation of influential measures. In particular, Cook and Kullback–Leibler distances are combined with their respective asymptotic results as well as to an alternative process of defining cut-off points. Some numerical examples illustrate how these measures are used in practice. We perform an application to simulated and actual data. Results provide evidence that the methodology based on Kullback–Leibler distance outperforms one in terms of the Cook classic distance. [ABSTRACT FROM AUTHOR]

Genetic algorithms (GAs), in the homogeneous as well as the non homogeneous version, have been widely used to solve combinatorial global optimization problems. Despite the successes that the non homogeneous GA (NHGA) encounters in practical applications, the theoretical results which guarantee the convergence of such algorithms are cited just in a few papers. There are, at least, three different ways of modeling GA as a Markov chain in order to study its convergence. In each approach, the transition matrices depend not only on the state space of the Markov chain but also on the way the genetic operators are defined. In this article, the extension to the non homogeneous case of the crossover operator which was based on neighborhoods is proposed, convergence results are presented, and numerical simulations in order to illustrate a comparative performance of the algorithms are developed. [ABSTRACT FROM PUBLISHER]

In the present paper, we are mainly concerned with the partially linear additive model defined, for a measurable function, bywhereZi= (Zi, 1, …,Zip)⊤andXi= (X1, i, …,Xid)⊤are vectors of explanatory variables,is a vector of unknown parameters,m1, …,mdare unknown univariate real functions, and ϵ1, …, ϵnare independent random errors with mean zero, finite variances σϵ, anda.s. We establish exact rates of strong uniform consistency of the non linear additive components of the model estimated by the marginal integration device with the kernel method. Our proofs are based upon the modern empirical process theory in the spirit of the works of Einmahl and Mason (2000) and Deheuvels and Mason (2004) relative to uniform deviations of non parametric kernel-type estimators. [ABSTRACT FROM PUBLISHER]

This paper is devoted to testing a classical periodic autoregressive against a periodic threshold autoregressive modelwith specified threshold. The local asymptotic normality property is shown via the adapted sufficient conditions due to Swensen (1985). Using this result we consider the case where the innovation density is specified, and we obtain a parametric local asymptotic “most stringent” test. [ABSTRACT FROM AUTHOR]

In this paper, we consider ak-out-of-nsystem consisting ofnidentical components with independent lifetimes. We show that when the underlying distribution functionF(t) is absolutely continuous, then it can be univocally determined by some particular mean residual lives or mean inactivity times of the system. It is then shown that these results may be extended to coherent (or mixed) systems. [ABSTRACT FROM AUTHOR]

This paper proposes a new model for autoregressive time series of counts in terms of a convolution of Poisson and negative binomial random variables, known as Poisson–negative binomial (PNB) distribution. The corresponding first-order integer valued time series models are developed and their properties are discussed. The geometric PNB and the geometric semi PNB distributions are also introduced and studied. [ABSTRACT FROM PUBLISHER]

The paper reviews finite mixture models for binomial counts with concomitant variables. These models are well known in theory, but they are rarely applied. We use a binomial finite mixture to model the number of credits gained by freshmen during the first year at the School of Economics of the University of Florence. The finite mixture approach allows us to appropriately account for the large number of zeroes and the multimodality of the observed distribution. Moreover, we rely on a concomitant variable specification to investigate the role of student background characteristics and of a compulsory pre-enrollment test in predicting gained credits. In the paper, we deal with model selection, including the choice of the number of components, and we devise numerical and graphical summaries of the model results in order to exploit the information content of the concomitant variable specification. The main finding is that the introduction of the pre-enrollment test gives additional information for student tutoring, even if the predictive power is modest. [ABSTRACT FROM PUBLISHER]

We discuss the use of variograms for covariance modeling under the Kriging model to assess tolerances on manufactured parts. The variogram is very informative about the spatial dependence and it is favored by researchers in the choice of a correlation function. It may give evidence of anisotropy and of nugget effect too. In this paper, various variogram estimators from literature are used for comparing and evaluating their properties in assessing the surface error of three workpieces manufactured with different machining precisions. Contrary to the common engineering belief, the variograms give evidence of both technological signatures and systematic errors of the measurement machines. [ABSTRACT FROM PUBLISHER]

For the exploratory analysis of three-way data, the Tucker3 is one of the most applied models to study three-way arrays when the data are quadrilinear. When the data consist of vectors of positive values summing to a unit, as in the case of compositional data, this model should consider the specific problems that compositional data analysis brings. The main purpose of this paper is to describe how to do a Tucker3 analysis of compositional data, and to show the relationships between the loading matrices when different preprocessing procedures are used. [ABSTRACT FROM PUBLISHER]

In this paper, through the monotonicity property of reversed hazards ratio, a new stochastic ordering is introduced. Two well-known parametric families of distributions are proved to be ordered with respect to their parameters, according to the new proposed stochastic order. Other situations, where the new order is applicable, are described in details. A number of elementary and basic properties of the order, for example, preservation under increasing transformations are derived. Stochastic comparisons of the parallel systems are made using the new stochastic order. In parallel with the obtained results, some examples will explain the concepts. [ABSTRACT FROM AUTHOR]

In this paper, we obtain an adjusted version of the likelihood ratio (LR) test for errors-in-variables multivariate linear regression models. The error terms are allowed to follow a multivariate distribution in the class of the elliptical distributions, which has the multivariate normal distribution as a special case. We derive a modifiedLRstatistic that follows a chi-squared distribution with a high degree of accuracy. Our results generalize those in Melo and Ferrari (Advances in Statistical Analysis, 2010,94, pp. 75–87) by allowing the parameter of interest to be vector-valued in the multivariate errors-in-variables model. We report a simulation study which shows that the proposed test displays superior finite sample behavior relative to the standardLRtest. [ABSTRACT FROM PUBLISHER]

In the conventional concept, the variance of a tolerance interval from the measurements is a single component, and the sample size for quality control process was estimated by the variance of a single component. However, we can find examples in recent about several components that could vary in their measurements, so an approximate method must be found to modify the conventional tolerance interval. In our paper, we develop an approach to calculate the sample size for a two-sided tolerance interval including several components in the variance from the measurements. An example is presented to illustrate our proposed method. [ABSTRACT FROM PUBLISHER]

In this paper, a new test for the equality of the mean vectors between a two groups with the same number of the observations in high-dimensional data. The existing tests for this problem require a strong condition on the population covariance matrix. The proposed test in this paper does not require such conditions for it. This test will be obtained in a general model, that is, the data need not be normally distributed. [ABSTRACT FROM PUBLISHER]

For the time-to-event outcome, current methods for sample determination are based on the proportional hazard model. However, if the proportionality assumption fails to capture the relationship between the hazard time and covariates, the proportional hazard model is not suitable to analyze survival data. The accelerated failure time (AFT) model is an alternative method to deal with survival data. In this paper, we address the issue that the relationship between the hazard time and the treatment effect is satisfied with the AFT model to design a multiregional trial. The log-rank test is employed to deal with the heterogeneous effect size among regions. The test statistic for the overall treatment effect is used to determine the total sample size for a multiregional trial, and the proposed criteria are used to rationalize partition sample size to each region. [ABSTRACT FROM PUBLISHER]

In this paper, we propose several approaches to estimate the parameters of the periodic first-order integer-valued autoregressive process with period T (PINAR(1)T) in the presence of missing data. By using incomplete data, we propose two approaches that are based on the conditional expectation and conditional likelihood to estimate the parameters of interest. Then we study three kinds of imputation methods for the missing data. The performances of these approaches are compared via simulations. [ABSTRACT FROM AUTHOR]

Filipiak and Markiewicz (2012) proved the universal optimality of circular weakly neighbor balanced designs (CWNBDs) under the interference model with fixed neighbor effects among the class of complete block designs. In two special cases where a CWNBD cannot exist, Filipiak et al. (2012) characterized D-optimal designs. The aim of this paper is to show the universal optimality of CWNBDs and to characterize D-optimal designs under the interference model with random neighbor effects. [ABSTRACT FROM AUTHOR]

The adaptive memory-type control charts, including the adaptive exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts, have gained considerable attention because of their excellent speed in providing overall good detection over a range of mean shift sizes. In this paper, we propose a new adaptive EWMA (AEWMA) chart using the auxiliary information for efficiently monitoring the infrequent changes in the process mean. The idea is to first estimate the unknown process mean shift using an auxiliary information based mean estimator, and then adaptively update the smoothing constant of the EWMA chart. Using extensive Monte Carlo simulations, the run length profiles of the AEWMA chart are computed and explored. The AEWMA chart is compared with the existing control charts, including the classical EWMA, CUSUM, synthetic EWMA and synthetic CUSUM charts, in terms of the run length characteristics. It turns out that the AEWMA chart performs uniformly better than these control charts when detecting a range of mean shift sizes. An illustrative example is also presented to demonstrate the working and implementation of the proposed and existing control charts. [ABSTRACT FROM AUTHOR]

This paper studies the optimal allocation of one active redundancy to a k-out-of-n system in the context of statistically dependent component lifetimes. It is proved that assigning the redundancy to the weakest component is more favorable so as to get a larger system lifetime in terms of both the usual stochastic order and the stochastic preference order. [ABSTRACT FROM AUTHOR]

In this paper, we consider a unified approach to stochastic comparisons of random vectors corresponding to two general multivariate mixture models. These stochastic comparisons are made with respect to multivariate hazard rate, reversed hazard rate and likelihood ratio orders. As an application, results are presented for stochastic comparisons of generalized multivariate frailty models. [ABSTRACT FROM AUTHOR]

In this paper, a new mixed sampling plan based on the process capability index (PCI) Cpk is proposed and the resultant plan is called mixed variable lot-size chain sampling plan (ChSP). The proposed mixed plan comprises of both attribute and variables inspections. The variable lot-size sampling plan can be used for inspection of attribute quality characteristics and for the inspection of measurable quality characteristics, the variables ChSP based on PCI will be used. We have considered both symmetric and asymmetric fraction non conforming cases for the variables ChSP. Tables are developed for determining the optimal parameters of the proposed mixed plan based on two points on the operating characteristic (OC) approach. In order to construct the tables, the problem is formulated as a non linear programming where the average sample number function is considered as an objective function to be minimized and the lot acceptance probabilities at acceptable quality level and limiting quality level under the OC curve are considered as constraints. The practical implementation of the proposed mixed sampling plan is explained with an illustrative real time example. Advantages of the proposed sampling plan are also discussed in terms of comparison with other existing sampling plans. [ABSTRACT FROM AUTHOR]

In order to avoid wrong conclusions in any further analysis, it is of importance to conduct a formal comparison for characteristic quantities of the distributions. These characteristic quantities we are familiar with include mean, quantity and reliability function, and so on. In this paper, we consider two tests aiming at the comparisons for function of parameters in Pareto distribution based on record values. They are generalized p-value-based test and parametric bootstrap-based test, respectively. The resulting procedures are easy to compute and are applicable to small samples. A simulation study is conducted to investigate and compare the performance of the proposed tests. A phenomenon we note is that generalized p-value-based test almost uniformly outperforms the parametric bootstrap-based test. [ABSTRACT FROM AUTHOR]

In this paper, we are proposing a modified jackknife Liu-type estimator (MJLTE) that was created by combining the ideas underlying both the Liu-type estimator (LTE) and the jackknifed Liu-type estimator (JLTE). We will also present the necessary and sufficient conditions for superiority of the MJLTE over the LTE and JLTE, in terms of mean square error matrix criterion. Finally, a real data example and a Monte Carlo simulation are also given to illustrate theoretical results. [ABSTRACT FROM PUBLISHER]

The aim of this paper is to propose a number of semiautomatic criteria for the joint selection of the model and the information set in the heteroskedastic context considered in Lejeune [Lejeune, B. (1997). Second order pseudo-maxim urn likelihood estimation and conditional variance misspecification. University of Liege. ERUDITE and CORE]. Particular cases of this methodology are the posterior information criterion (PIC) and the posterior information criterion for a forecasts (PICF) of Phillips [Phillips. P. C. B. (1996). Econometric model determination. Econometrica 64:763-812] and Phillips and Ploberger [Phillips. P. C. B., Ploberger. W. (1994). Posterior odds testing for a unit root with data-based model setection. Econometric Theory 10:774-808] and the Bayesian information criterion (BIC) criterion of Schwarz [Schwarz. G. (1978). Estimating the dimension of a model. Ann, Statist, 6:461-464]. Sufficient conditions for the weak and strong consistencies of the proposed criteria are provided. Furthermore, the behaviors of these criteria are analyzed in the presence of sinieturat changes. [ABSTRACT FROM AUTHOR]

In this paper, we consider the univariate generalized t (GT) distribution, which is introduced by McDonald and Newey ((1988) Partially adaptive estimation of regression models via the generalized t distribution. Econometric Theory 4:428-457.). We show that the maximum likelihood estimators for the location and the scale parameters of a GT distribution with known shape parameters can provide alternative robust estimators for the location and scale parameters of a data set. We investigate the existence and the uniqueness of the maximum likelihood estimators. We show that the likelihood function can be unimodal or multimodal depending on the different choices of the shape parameters. [ABSTRACT FROM AUTHOR]

In this paper, the focus is on sequential analysis of multivariate financial time series with heavy tails. The mean vector and the covariance matrix of multivariate non linear models are simultaneously monitored by modifying conventional control charts to identify structural changes in the data. The considered target process is a constant conditional correlation model (cf. Bollerslev, 1990), an extended constant conditional correlation model (cf. He and Teräsvirta, 2004), a dynamic conditional correlation model (cf. Engle, 2002), or a generalized dynamic conditional correlation model (cf. Capiello et al., 2006). For statistical surveillance we use control charts based on residuals. Further, the procedures are constructed fort-distribution. The detection speed of these charts is compared via Monte Carlo simulation. In the empirical study, the procedure with the best performance is applied to log-returns of the stock market indices FTSE and CAC. [ABSTRACT FROM PUBLISHER]

This paper introduces several forms of nested bivariate zero-inflated generalized Poisson (BZIGP) regression model which can be fitted to bivariate and zero-inflated count data. The main advantage of having several forms of BZIGP regression model is that they are nested and allow likelihood ratio test to be performed for choosing the best model. In addition, the BZIGP regression models have flexible forms of marginal mean–variance relationship, can be fitted to bivariate and zero-inflated count data with positive or negative correlations, and allow additional overdispersion of the two response variables. The BZIGP regression models are fitted to the Australian Health Survey data. [ABSTRACT FROM AUTHOR]

Based on record values, point and interval estimators are proposed in this paper for the parameters of a general lower-truncated family of distributions. Maximum likelihood and bias-corrected estimators are obtained for unknown model parameters. Based on a sufficient and complete statistic, the bias-corrected estimator is also shown to be uniformly minimum variance unbiased estimator. Different exact confidence intervals and exact confidence regions are constructed for the both model and truncated parameters, and other confidence interval estimates based on asymptotic distribution theory and bootstrap approaches are obtained as well. Finally, two real-life examples and a numerical study are presented to illustrate the performance of our methods. [ABSTRACT FROM AUTHOR]

In this paper we propose a general cure rate aging model. Our approach enables different underlying activation mechanisms which lead to the event of interest. The number of competing causes of the event of interest is assumed to follow a logarithmic distribution. The model is parameterized in terms of the cured fraction which is then linked to covariates. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis for the proposed model. Moreover, some discussions on the model selection to compare the fitted models are given, as well as case deletion influence diagnostics are developed for the joint posterior distribution based on the ψ-divergence, which has several divergence measures as particular cases, such as the Kullback–Leibler (K-L),J-distance,L1norm, and χ2-square divergence measures. Simulation studies are performed and experimental results are illustrated based on a real malignant melanoma data. [ABSTRACT FROM AUTHOR]

By releasing the unbiasedness condition, we often obtain more accurate estimators due to the bias–variance trade-off. In this paper, we propose a class of shrinkage proportion estimators which show improved performance over the sample proportion. We provide the “optimal” amount of shrinkage. The advantage of the proposed estimators is given theoretically as well as explored empirically by simulation studies and real data analyses. [ABSTRACT FROM AUTHOR]

In this paper, the problem of comparing t test lines with a control line under a row–column setup in complete diallel cross experiment is investigated when specific combining ability (sca) effect is included in the model. Three classes of Mating-Environmental Row–Column (MERC) designs have been obtained which are variance balanced for estimating the contrasts pertaining to general combining ability (gca) effects free fromscaeffects. [ABSTRACT FROM AUTHOR]