vol. 11 núm. 1 (2018)

Editorial, número 11 volumen 1

We propose a construction of coincident index for Colombian economic by using common factors of a set of macroeconomic variables and the coincident profile approach to select one of them, as the closest to the state of the economy.

Student teacher evaluation is the most commonly used method in latin american universities to evaluate the quality of teaching provided by teachers. Bearing this reference in mind, the present article gives an account of how a multivariate analysis was applied to the questionnaire used by the Universidad Santo Tom´as in Bogot´a during the 2012-2014 periods. This work included a reliability analysis, an exploratory and confirmatory factorial analysis to evaluate the validity, reliability and dimensionality of the instrument with which teachers are evaluated. In addition, the relationship between teacher performance and student performance was assessed. A mixed classification analysis was carried out to characterize the results obtained at different levels (divisions, faculties and professors). Finally, a performance perception index was constructed for the faculties according to the students. Among the most outstanding results we find that the proposed instrument is valid and reliable, however, two items need to be adjusted. It was also noted that the student’s grade toward the teacher is not related to the student’s final grade. In the classification of teachers, three groups of teachers were found, differentiating between low, medium and high performing teachers according to the students. Among the items that best discriminate against the three groups are that “the teacher uses educational aids that enhance learning” and that “the teacher applies methodological strategies that favour learning”. It was shown that the perception of teachers’ performance by students is higher than 78 %. These results allowed the implementation of pedagogical strategies to improve teaching work in the university.

In this work, we consider a Bayesian hierarchical space-time model for concentration of particulate matter 2.5 in the City of Santiago de Chile proposed by (Cameletti et al. 2013). Taking into consideration the covariates: daily mean temperature, daily mean relative humidity, daily mean wind speed and spatial geographic coordinates. The data were measured in 11 air quality monitoring stations in the City of Santiago, recorded by hour during the years 2012, 2013 and 2014. The recopilaty information, we build prediction maps of the particulate material 2.5 and probability maps of exceeding the allowed threshold. The calculations were performed in the software the R-library INLA.

This article presents the evaluation of Colombian bamboo fibres as a reinforce material in the polymer matrix created with a mixture of High Density-Polyethylene and a commercial coupling agent (polybond 1009). Through a 23 factorial design it was studied the differences between a composite material (polyethylene and Colombian bamboo) and the base material (High Density-Polyethylene) for different mechanical properties.As a result, the composite material has a 45 % reduction in impact strength and a 49 % increase in tensile strength when is compared to the base material. It is important to note that, despite having less impact resistance, the modulus of elasticity of the composite material increases by 234 %, which is important evidence of the role of guadua fibers as a reinforcing material.

Data obtained from variables measured as percentages, rates and proportions are called proportional data and these variables are usually within the (0,1) interval. Although, different distributions have been developed to characterize these variables, it is possible that some variables take the extreme values at zero and one. Some researchers as Ospina & Ferrari (2012) and Rigby & Stasinopoulos (2005) proposed the inflated Beta distribution with zeros and/or ones, differentiated only by their parameterization. Other authors such as Galvis & Lachos (2014) have worked with inflated proportional data, considering other distributions such as simplex distributions. Nevertheless, it has not been found any distribution which combines the main characteristic of several distributions for solving these issue. Thus, this paper presents the ZOIP package (Zeros Ones Inflated Proportional), developed on the computation system R, this package combines both Beta and simplex distribution and estimates its parameters given the parameters for the original distributions. The parameters estimation process, is performed by maximum likelihood method. Finally, simulations studies have been performed which show the accuracy of the parameters convergence and the adjustment of a ZOIP distribution on real data

Spatial models that smooth standardized mortality ratios are widely used in disease mapping. Usually, estimation is imprecise when events are rare. In situations where each areal count splits into different time periods, this problem is more evident because of the presence of even lower counts for the areal units for each time period. In this work, we analyze models that include geographic and temporal information and some covariates such as percentage of urban household, percentage of people between 24 and 49 years old, and infant mortality ratio of each county in 2011. As a result, these models produce better estimations, especially for the model with the simplest space-time interaction. Finally, HIV/AIDS mortality data in Costa Rica (1998-2012) are used as an illustration to compare classic standardized mortality ratios and posterior means of relative risk. The proposed method is more efficient and more precise than the maximum likelihood.

In this paper we analyze the performance of the confidence intervals estimation via normal approximation and parametric bootstrap for the parameters of the Weibull distribution in eighteen simulated scenarios. Under different sample sizes, the effect of the form parameter β on the interval estimate is evaluated for the scale parameter η. In the same way, the scale parameter is varied in the interval estimation for the shape parameter. We found that the confidence intervals constructed under the bootstrap approach show a better behavior in comparison with those obtained by normal approximation in terms of coverage probability and median length. The confidence intervals at (1 −α)×100 % by normal approximation for β were asymmetric with respect to the error α. In both methods, it is evident that for β ≥ 2 the confidence intervals for the parameter η decrease the length.