The modified slash Lindley–Weibull distribution with applications to nutrition data

This work presents an extension of the slash Lindley–Weibull distribution, of which it can be considered a modification. The new family is obtained by using the quotient of two independent random variables: a two-parameter Lindley–Weibull distribution divided by a power of the exponential distribution with parameter equal to 2. We present the pdf and cdf of the new distribution, analyzing their risk functions. Some statistical properties are studied and the moments and coefficients of asymmetry and kurtosis are shown. The parameter estimation problem is carried out by the maximum likelihood method. The method is assessed by a Monte Carlo simulation study. We use nutrition data, which are characterized by high kurtosis, to illustrate the usefulness of the proposed model.     

Forecasting Multivariate Road Traffic Flows Using Bayesian Dynamic Graphical Models,Splines and Other Traffic Variables

Traffic flow data are routinely collected for many networks worldwide. These invariably large data sets can be used as part of a traffic management system, for which good traffic flow forecasting models are crucial. The linear multiregression dynamic model (LMDM) has been shown to be promising for forecasting flows, accommodating multivariate flow time series, while being a computationally simple model to use. While statistical flow forecasting models usually base their forecasts on flow data alone, data for other traffic variables are also routinely collected. This paper shows how cubic splines can be used to incorporate extra variables into the LMDM in order to enhance flow forecasts. Cubic splines are also introduced into the LMDM to parsimoniously accommodate the daily cycle exhibited by traffic flows. The proposed methodology allows the LMDM to provide more accurate forecasts when forecasting flows in a real high‐dimensional traffic data set. The resulting extended LMDM can deal with some important traffic modelling issues not usually considered in flow forecasting models. Additionally, the model can be implemented in a real‐time environment, a crucial requirement for traffic management systems designed to support decisions and actions to alleviate congestion and keep traffic flowing.     

Financial Well-Being Index in México

Social Indicators Research - This paper aims to construct a financial well-being index and analyze its determinants among adults in Mexico. It employs multiple correspondence analysis, multiple...     

Bimodality based on the generalized skew-normal distribution

This paper focuses on the development of a new extension of the generalized skew-normal distribution introduced in Gómez et al. [Generalized skew-normal models: properties and inference. Statistics. 2006;40(6):495–505]. To produce the generalization a new parameter is introduced, the signal of which has the flexibility of yielding unimodal as well as bimodal distributions. We study its properties, derive a stochastic representation and state some expressions that facilitate moments derivation. Maximum likelihood is implemented via the EM algorithm which is based on the stochastic representation derived. We show that the Fisher information matrix is singular and discuss ways of getting round this problem. An illustration using real data reveals that the model can capture well special data features such as bimodality and asymmetry.     

The Tanda: A Practice at the Intersection of Mathematics,Culture, and Financial Goals

We present an analysis and discussion of the tanda, a multiperson pooled credit and savings scheme (a rotating credit association or RCA), as described by two informants from Mexican immigrant communities in California. In the tanda, participants contribute regularly to a common fund which is distributed to participants on a rotating basis. We analyze the tanda at multiple levels (as a mathematical, cultural, and distributed practice) and identify points of intersection and conflict. Contrary to many formal or school-based conceptions of mathematics, mathematical work in the context of the tanda is in service of, and intimately tied up with, cultural goals and values. Likewise, cultural means and mathematics are employed to personal ends. We argue that the tanda should be of enduring interest, particularly among educators interested in bringing more authentic, culturally-relevant mathematics into classroom settings, because it so clearly illustrates how mathematical and cultural processes can interact in the context of personal goals, and provides a potentially valuable template for engaging, consequential, and successful mathematics.     

Joint models for mixed categorical outcomes: a study of HIV risk perception and disease status in Mozambique

Two types of bivariate models for categorical response variables are introduced to deal with special categories such as ‘unsure’ or ‘unknown’ in combination with other ordinal categories, while taking additional hierarchical data structures into account. The latter is achieved by the use of different covariance structures for a trivariate random effect. The models are applied to data from the INSIDA survey, where interest goes to the effect of covariates on the association between HIV risk perception (quadrinomial with an ‘unknown risk’ category) and HIV infection status (binary). The final model combines continuation-ratio with cumulative link logits for the risk perception, together with partly correlated and partly shared trivariate random effects for the household level. The results indicate that only age has a significant effect on the association between HIV risk perception and infection status. The proposed models may be useful in various fields of application such as social and biomedical sciences, epidemiology and public health.     

L'analyse de la variation saisonniére quand l'amplitude et la taille sont faibles

Studies of seasonal variation are valuable in biomedical research because they can help to discover the etiology of diseases that are not well understood. Generally in these studies the data have certain characteristics that require specialized tests and methods for the statistical analysis. But the effectiveness of these specialized tests is variable, especially according to the seasonal variation, the dimension of the amplitude in the seasonal variation, and the sample size. The purpose of this paper is to present a test and methods appropriate for the analysis and modeling of data whose seasonal variation has small amplitude and whose sample size is small. This test can detect different kinds of seasonal variation. The results from a simulation study show that the test performs very well. The application of these methods is illustrated by two examples.     

LATIN AMERICA'S DECLINING SKILL PREMIUM: A MACROECONOMIC ANALYSIS

The decline in Latin America's skill premium and income inequality during the 2000s was partly driven by an economic expansion that favored low‐skill‐intensive service sectors. Evidence shows inequality becomes countercyclical in the 2000s, and unlike previous expansions, the boom was concentrated on services while manufacturing lagged behind. I build an open economy general equilibrium model that features a low‐skill‐intensive nontradable sector. The model suggests that favorable shocks to commodity prices and international interest rate spreads, such as those that buffeted Latin America in the 2000s, account for about a fifth of the observed decline in the skill premium. (JEL D31, E32, F41, O15, O54)     

A Neuropsychoanalytic Approach to Case Studies

Neuropsychoanalysis is an interdisciplinary field that attempts to generate links between psychoanalytic schools and the neurosciences. Historically speaking, neuropsychoanalysis emerged as a response to ‘cognitive’ views of the mind/brain problem, which tended to neglect the influence of emotional and instinctual processes in the constitution, and functioning, of the human mind. Since its origins, neuropsychoanalysis has used case studies, of brain injured individuals undergoing psychoanalytic treatment, to explore how focal damage to specific brain areas is related to changes in non-cognitive domains of the mind, such as emotion, motivation or personality. This approach is a useful contribution to the neurosciences since it allows observing, at the same time, objective and subjective aspects of the mind/brain, thus bridging third and first person methodologies. In this article a neuropsychoanalytic approach to case studies is introduced, describing both its historical roots as well as its present status. Then, a brief case study, of a man with focal damage to the left dorso-lateral prefrontal cortex, who presented with changes in his capacity to intrinsically regulate feelings, is used to exemplify this approach.