The effectiveness of a group-based educational program on the self-efficacy and self-acceptance of menopausal women: A randomized controlled trial

This study aimed to assess the effectiveness of a group-based educational training on the self-efficacy and self-acceptance of Iranian menopausal women using the PRECEDE–PROCEED model. This Randomized Controlled Trial (RCT) was conducted on 80 menopausal women in the age range of 47–55 years residing in the northeast of Iran. The participants were divided randomly into a test group (n = 40) and a control group (n = 40). We found that designing and implementation of a group-based educational training according to the PRECEDE–PROCEED model can significantly enhance the knowledge and performance of the test group with regard to self-efficacy and self-acceptance.     

An inventory model with random discount offerings

We consider an inventory model in which a supplier makes deal offers with random discount prices at random points in time. Assuming that discount offerings follow a Poisson process and discount price is a discrete random variable with a known distribution, we propose a continuous-review control policy for the model and derive optimality conditions for the policy parameters. The model is then extended to the case of multiple suppliers that offer discount deals with supplier-specific Poisson processes and discount prices. Numerical examples are presented to demonstrate cost savings due to discount offers.     

Some Modifications for Choosing Ridge Parameters

Standard least square regression can produce estimates having a large mean squares error (MSE) when predictor variables are highly correlated or multicollinear. In this article, we propose four modifications to choose the ridge parameter (K) when multicollinearity exists among the columns of the design matrix. The proposed new estimators are extended versions of that suggested by Khalaf and Shukur (2005 Khalaf , G. , Shukur , G. ( 2005 ). Choosing ridge parameter for regression problems . Commun. Statist. A 34 : 1177 – 1182 . [CSA] [Taylor & Francis Online] , [Google Scholar]). The properties of these estimators are compared with those of Hoerl and Kennard (1970a Hoerl , A. E. , Kennard , R. W. ( 1970a ). Ridge regression: biased estimation for non-orthogonal problems . Tech. . 12 : 55 – 67 . [CSA] [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) and the OLS using the MSE criterion. All estimators under consideration are evaluated using simulation techniques under certain conditions where a number of factors that may affect their properties have been varied. In addition, it is shown that at least one of the proposed estimators either has a smaller MSE than the others or is the next best otherwise.     

Mixture of the Riesz Distribution with Respect to a Multivariate Poisson

The aim of this article is to study a statistical model obtained by the mixture of the Riesz probability distribution on symmetric matrices with respect to a multivariate Poisson distribution. We show that this distribution is related to the modified Bessel function of the first kind. We then determine the domain of the means and the variance function of the generated natural exponential family.     

Shrinkage ridge regression in partial linear models

ABSTRACT

In this paper, shrinkage ridge estimator and its positive part are defined for the regression coefficient vector in a partial linear model. The differencing approach is used to enjoy the ease of parameter estimation after removing the non parametric part of the model. The exact risk expressions in addition to biases are derived for the estimators under study and the region of optimality of each estimator is exactly determined. The performance of the estimators is evaluated by simulated as well as real data sets.     

Evidential inference and optimal sample size determination on the basis of record values and record times under random sampling scheme

In this paper, the likelihood ratio approach is applied for measuring evidence provided by record data in favor of a hypothesis against an alternative under a random sampling scheme. Explicit expressions for probabilities of observing strong and weak evidences are derived. Asymptotic behaviors of these probabilities are investigated in a greater detail. Optimal sample size in which the substantial evidence reaches a desired level is determined. An illustrative example concerning records of times between consecutive telephone calls to a company’s switchboard is also analyzed.     

The minimum value of geometric-arithmetic index of graphs with minimum degree 2

The geometric-arithmetic index was introduced in the chemical graph theory and it has shown to be applicable. The aim of this paper is to obtain the extremal graphs with respect to the geometric-arithmetic index among all graphs with minimum degree 2. Let G(2, n) be the set of connected simple graphs on n vertices with minimum degree 2. We use linear programming formulation and prove that the minimum value of the first geometric-arithmetic \((GA_{1})\) index of G(2, n) is obtained by the following formula:

$$\begin{aligned} GA_1^* = \left\{ \begin{array}{ll} n&{}\quad n \le 24, \\ \mathrm{{24}}\mathrm{{.79}}&{}\quad n = 25, \\ \frac{{4\left( {n - 2} \right) \sqrt{2\left( {n - 2} \right) } }}{n}&{}\quad n \ge 26. \\ \end{array} \right. \end{aligned}$$

     

Efficiency of the generalized difference-based Liu estimators in semiparametric regression models with correlated errors

In this paper, a generalized difference-based estimator is introduced for the vector parameter β in the semiparametric regression model when the errors are correlated. A generalized difference-based Liu estimator is defined for the vector parameter β in the semiparametric regression model. Under the linear nonstochastic constraint Rβ=r, the generalized restricted difference-based Liu estimator is given. The risk function for the β?_GRD(η) associated with weighted balanced loss function is presented. The performance of the proposed estimators is evaluated by a simulated data set.     

On the Benefits of Risk Pooling in Inventory Management

We analyze the benefits of inventory pooling in a multi‐location newsvendor framework. Using a number of common demand distributions, as well as the distribution‐free approximation, we compare the centralized (pooled) system with the decentralized (non‐pooled) system. We investigate the sensitivity of the absolute and relative reduction in costs to the variability of demand and to the number of locations (facilities) being pooled. We show that for the distributions considered, the absolute benefit of risk pooling increases with variability, and the relative benefit stays fairly constant, as long as the coefficient of variation of demand stays in the low range. However, under high‐variability conditions, both measures decrease to zero as the demand variability is increased. We show, through analytical results and computational experiments, that these effects are due to the different operating regimes exhibited by the system under different levels of variability: as the variability is increased, the system switches from the normal operation to the effective and then complete shutdown regimes; the decrease in the benefits of risk pooling is associated with the two latter stages. The centralization allows the system to remain in the normal operation regime under higher levels of variability compared to the decentralized system.