BackgroundAn adequate forecasting model of mortality that allows an analysis of different population changes is a topic of interest for countries in demographic transition. Phenomena such as the reduction of mortality, ageing, and the increase in life expectancy are extremely useful in the planning of public policies that seek to promote the economic and social development of countries. To our knowledge, this paper is one of the first to evaluate the performance of mortality forecasting models applied to abridged life tables.ObjectiveSelect a mortality model that best describes and forecasts the characteristics of mortality in Colombia when only abridged life tables are available.Data and methodWe used Colombian abridged life tables for the period 1973–2005 with data from the Latin American Human Mortality Database. Different mortality models to deal with modeling and forecasting probability of death are presented in this study. For the comparison of mortality models, two criteria were analyzed: graphical residuals analysis and the hold-out method to evaluate the predictive performance of the models, applying different goodness of fit measures.ResultsOnly three models did not have convergence problems: Lee-Carter (LC), Lee-Carter with two terms (LC2), and Age-Period-Cohort (APC) models. All models fit better for women, the improvement of LC2 on LC is mostly for central ages for men, and the APC model’s fit is worse than the other two. The analysis of the standardized deviance residuals allows us to deduce that the models that reasonably fit the Colombian mortality data are LC and LC2. The major residuals correspond to children’s ages and later ages for both sexes.ConclusionThe LC and LC2 models present better goodness of fit, identifying the principal characteristics of mortality for Colombia.Mortality forecasting from abridged life tables by sex has clear added value for studying differences between developing countries and convergence/divergence of demographic changes.

<p>This study evaluated different models and proposed a reliable and accurate model using non-destructive measurements of leaf length (L) and/or width (W) for estimating the leaf area of <em>Tithonia diversifolia</em> (TD). Rapid, reliable and objective estimation of the leaf area is essential for numerous studies in agronomy and plant physiology, however, it is done usually by the availability of sophisticated and expensive electronic integrate methods. Allometric equations were developed by measuring W, L and LA of 92 leaves of TD, by a linear regression analysis. The current leaf area was measured using <em>ImageJ</em> software. With the observed and estimated information, a Pearson correlation analysis was performed. Pearson correlation coefficients oscillated between 0.93-0.94 for the best mathematical models. Equations which used as variable the product L*W presented strong relationships with the observed leaf area, manifested in high determination coefficients (R² = 0.89). Therefore, the use of the product of L*W as the independent variable was found to be accurate to predict the TD leaf area. In conclusion, a lineal model was developed to predict the leaf area for the <em>T. diversifolia</em> (y=0.755+0.438(W*L).</p>