An empirical comparison of EM,SEM and MCMC performance for problematic Gaussian mixture likelihoods

We compare EM, SEM, and MCMC algorithms to estimate the parameters of the Gaussian mixture model. We focus on problems in estimation arising from the likelihood function having a sharp ridge or saddle points. We use both synthetic and empirical data with those features. The comparison includes Bayesian approaches with different prior specifications and various procedures to deal with label switching. Although the solutions provided by these stochastic algorithms are more often degenerate, we conclude that SEM and MCMC may display faster convergence and improve the ability to locate the global maximum of the likelihood function.     

Planning for a new international economic order?

Many a familiar planning instrument seems buried in the hot desert of the Persian Gulf: extrapolations, forecasts and projections. The corporate planner is now highly environmentally oriented. If he has recovered from the energy crisis, is conversant with the food emergency, and resigned to persistent inflation—he is about to face a new and unfamiliar phenomenon. It is ambitiously called “the new international economic order” (for the sake of brevity: NIEO).     

Future demand patterns in the emerging world

The author examines the implications of the inter-dependence of nations, particularly vis-à-vis the Third World. He argues that those emerging countries which wish to progress socially, politically and economically in the next twenty years may have to promote new and daring development patterns. Further, marketing managers who wish to prepare their future operations in that emerging world will need to be as venturesome in new planning tools. He suggests that Taxonomy, used creatively, might be that instrument.     

What is driving increasing child welfare caseloads in Ontario? Analysis of the 1993 and 1998 Ontario incidence studies

Rates of substantiated maltreatment documented by the 1993 and 1998 Ontario Incidence Studies of Reported Child Abuse and Neglect doubled between 1993 and 1998. Although increasing public awareness and changes in investigation procedures appear to account for part of this change, the increase also reflects a significant shift in the types of maltreatment agencies are investigating and substantiating. Exposure to spousal violence has increased eightfold, and the proportion of neglect cases has more than doubled, whereas cases of sexual abuse are decreasing. The field requires a differentiated response to address the maltreatment-specific challenges underlying child welfare caseload increases in Canada.     

On elliptical multilevel models

Multilevel models have been widely applied to analyze data sets which present some hierarchical structure. In this paper we propose a generalization of the normal multilevel models, named elliptical multilevel models. This proposal suggests the use of distributions in the elliptical class, thus involving all symmetric continuous distributions, including the normal distribution as a particular case. Elliptical distributions may have lighter or heavier tails than the normal ones. In the case of normal error models with the presence of outlying observations, heavy-tailed error models may be applied to accommodate such observations. In particular, we discuss some aspects of the elliptical multilevel models, such as maximum likelihood estimation and residual analysis to assess features related to the fitting and the model assumptions. Finally, two motivating examples analyzed under normal multilevel models are reanalyzed under Student-t and power exponential multilevel models. Comparisons with the normal multilevel model are performed by using residual analysis.     

Diagnostics in multivariate generalized Birnbaum-Saunders regression models

Birnbaum–Saunders (BS) models are receiving considerable attention in the literature. Multivariate regression models are a useful tool of the multivariate analysis, which takes into account the correlation between variables. Diagnostic analysis is an important aspect to be considered in the statistical modeling. In this paper, we formulate multivariate generalized BS regression models and carry out a diagnostic analysis for these models. We consider the Mahalanobis distance as a global influence measure to detect multivariate outliers and use it for evaluating the adequacy of the distributional assumption. We also consider the local influence approach and study how a perturbation may impact on the estimation of model parameters. We implement the obtained results in the R software, which are illustrated with real-world multivariate data to show their potential applications.     

Collinearity diagnostic applied in ridge estimation through the variance inflation factor

The variance inflation factor (VIF) is used to detect the presence of linear relationships between two or more independent variables (i.e. collinearity) in the multiple linear regression model. However, the traditionally used VIF definitions encounter some problems when extended to the case of the ridge estimation (RE). This paper presents an extension of the VIF in RE by providing two alternative VIF expressions that overcome these problems in the general case. Some characteristics of these expressions are also presented and compared with the traditional expression. The results are illustrated with an economic example in the case of three independent variables and with a Monte Carlo simulation for the general case.     

Sequential voting by veto: Making the Mueller-Moulin algorithm more versatile

This paper shows that a relatively easy algorithm for computing the (unique) outcome of a sophisticated voting procedure called sequential voting by veto (SVV) applies to a more general situation than considered hitherto. According to this procedure a sequence of n voters must select s out of m + s options (s > 0, m 3 n 3 2). The ith voter, when his turn comes, vetoes k _i options (k _i 1, k _i = m). The s remaining non-vetoed options are selected. Every voter is assumed to be fully informed of all other voters total (linear) preference orderings among the competing options, as well as of the order in which the veto votes are cast. This algorithm was proposed by Mueller (1978) for the special case where s and the k _i are all equal to 1, and extended by Moulin (1983) to the somewhat more general case where the k _i are arbitrary but s is still 1. Some theoretical and practical issues of voting by veto are discussed.     

Selection of Logistic Service Providers for the transportation of refrigerated goods

The aim of this article is to propose a decision model based on Analytic Hierarchy Process (AHP) for the evaluation and selection of Logistics Service Providers (LSPs) for a refrigerated products company. The results indicated that quality, responsiveness and reliability are the most important criteria for selecting an LSP for the transportation of perishable refrigerated goods, considering contractor’s profile, which is based on protection of its brand and reputation in the market. In addition, sensitivity analysis is performed to verify priority ranking stability. Therefore, this research illustrates how AHP model could be implemented to help the decision-making process for selecting third-party services in logistics for perishable refrigerated goods effectively.