Effect of autocorrelation when estimating the trend of a time series via penalized least squares with controlled smoothness

This paper studies the effect of autocorrelation on the smoothness of the trend of a univariate time series estimated by means of penalized least squares. An index of smoothness is deduced for the case of a time series represented by a signal-plus-noise model, where the noise follows an autoregressive process of order one. This index is useful for measuring the distortion of the amount of smoothness by incorporating the effect of autocorrelation. Different autocorrelation values are used to appreciate the numerical effect on smoothness for estimated trends of time series with different sample sizes. For comparative purposes, several graphs of two simulated time series are presented, where the estimated trend is compared with and without autocorrelation in the noise. Some findings are as follows, on the one hand, when the autocorrelation is negative (no matter how large) or positive but small, the estimated trend gets very close to the true trend. Even in this case, the estimation is improved by fixing the index of smoothness according to the sample size. On the other hand, when the autocorrelation is positive and large the simulated and estimated trends lie far away from the true trend. This situation is mitigated by fixing an appropriate index of smoothness for the estimated trend in accordance to the sample size at hand. Finally, an empirical example serves to illustrate the use of the smoothness index when estimating the trend of Mexico’s quarterly GDP.     

A geostatistical approach to define guidelines for radon prone area identification

Radon is a natural radioactive gas known to be the main contributor to natural background radiation exposure and the major leading cause of lung cancer second to smoking. Indoor radon concentration levels of 200 and 400 Bq/m³ are reference values suggested by the 90/143/Euratom recommendation, above which mitigation measures should be taken in new and old buildings, respectively, to reduce exposure to radon. Despite this international recommendation, Italy still does not have mandatory regulations or guidelines to deal with radon in dwellings. Monitoring surveys have been undertaken in a number of western European countries in order to assess the exposure of people to this radioactive gas and to identify radon prone areas. However, such campaigns provide concentration values in each single dwelling included in the sample, while it is often necessary to provide measures of the pollutant concentration which refer to sub-areas of the region under study. This requires a realignment of the spatial data from the level at which they are collected (points) to the level at which they are necessary (areas). This is known as change of support problem.In this paper, we propose a methodology based on geostatistical simulations in order to solve this problem and to identify radon prone areas which may be suggested for national guidelines.     

First Exits from the Swedish Labor Market Due to Disability

Nowadays, with an increasingly aging population, an increasing proportion of the population on disability benefits, and an implicitly lower level of economic output and foregone tax revenue, disability has become a major public policy issue in many countries. Estimating both single risk and competing risks models on a Swedish longitudinal database, this study analyzes the risk of exit from the labor market due to disability at a certain age, conditional on having remained in the labor force until that age. The explanatory variables did not have identical coefficients across destination types. For example, the estimated single risk model shows that a higher level of education decreased the hazard of exiting the labor market with a disability pension, while the estimated competing risks model suggests that a higher level of education increased the hazard of exiting with a partial disability pension, but it decreased the hazard of exiting with a full disability pension.

Theoriegeleitetes Sampling für international vergleichende Mixed-Methods-Forschung

The paper motivates a mixed design for investigating the gender division of labour at the life course transition to parenthood and describes how the design has been realised. The focus is on the sampling strategy which aims to combine two longitudinal methods. Each method is applied in international comparative perspective. The sampling is crucial, for both facilitating the comparison and integrating the research findings. The complementary research design aims at systematically linking social structure to the re-production of gendered divisions of labour and its subjective meanings for dual earner parents. Context-related analysis of qualitative interviews in an explicit comparative design, combined with an analysis of structural patterns of action shows that the agency of expectant parents rises with congruence of dominant gender ideologies and family policies.     

Organizational Wellbeing in CSOs in Morelos (Mexico): Findings from a Qualitative Study

In recent years, civil society organizations (CSOs) have become a significant aspect of Mexican reality given the number of people involved in them and their contribution to the services sector. These entities are organizations where voluntary and paid workers may experience wellbeing conditions that are inherent in empowerment processes, feelings of usefulness, and the satisfaction associated with participating in decision-making. At the same time, contradictory dynamics related to governance, power relations, leadership, and decision-making may be activated in CSOs and create uncertainty and psychosocial malaise. In this research, based on a grounded theory approach, 11 interviews and 89 questionnaires were realized in 14 service-providing CSOs in the Mexican State of Morelos, highlighting the wellbeing/malaise dimensions and psychosocial factors that are relevant for their members.     

Markov random field-based image subsampling method

The use of Bayesian models for the reconstruction of images degraded by both some blurring function H and the presence of noise has become popular in recent years. Making an analogy between classical degradation processes and resampling, we propose a Bayesian model for generating finer resolution images. The approach involves defining resampling, or aggregation, as a linear operator applied to an original picture to produce derived lower resolution data which represent our available experimental infor-mation. Within this framework, the operation of making inference on the orginal data can be viewed as an inverse linear transformation problem. This problem, formalized through Bayes' theorem, can be solved by the classical maximum a posteriori estimation procedure. Image local characteristics are assumed to follow a Gaussian Markov random field. Under some mild assumptions, simple, iterative and local operations are involved, making parallel 'relaxation' processing feasible. experimental results are shown on some images, for which good subsampling estimates are obtained.     

Anonymous and neutral majority rules

In the standard arrovian framework and under the assumption that individual preferences and social outcomes are linear orders on the set of alternatives, we provide necessary and sufficient conditions for the existence of anonymous and neutral rules and for the existence of anonymous and neutral majority rules. We also determine a general method for constructing and counting these rules and we explicitly apply it to some simple cases.     

Schlägt Wissen Funken? Zu den Effekten des politischen Steuerungsinstruments Sparkling Science

Although knowledge is attributed a high societal value, its traditional ‘production’ in academia as well as its traditional ‘consumption’ in education have increasingly become problematic. Austrian politics have launched a rather unconventional political steering instrument to solve this problem: Sparkling Science. Based on the equal involvement of pupils and scientists in research projects, this program aims to create ‘sparks of enthusiasm’ as well as ‘sparks of innovation’ between academia and education. We inquire into the effects of this political steering instrument on the level of individual actors. Drawing on qualitative data from a case study, our analyses identify a structural composition that alters the two explicit objectives, which are: To increase pupil’s enthusiasm for science and to stimulate innovative research based on multiple perspectives.     

Roundoff error for floating point representation of real data

In the present paper we define aprobabilistic model for the study ofthe relative roundoff error in the floating point representation ofreal data. In particular, starting from the assumption that real data is uniformly distributed in the interval (0,1), each floating point is assigned aprobability value corresponding to the proportion of real data assigned this floating point value. For each real number x～ U(0,1), we compute the relative roundoff error in the floating point representation and we calculate i t s expected value and variance.