Estimation and inference under economic restrictions

Estimation of economic relationships often requires imposition of constraints such as positivity or monotonicity on each observation. Methods to impose such constraints, however, vary depending upon the estimation technique employed. We describe a general methodology to impose (observation-specific) constraints for the class of linear regression estimators using a method known as constraint weighted bootstrapping. While this method has received attention in the nonparametric regression literature, we show how it can be applied for both parametric and nonparametric estimators. A benefit of this method is that imposing numerous constraints simultaneously can be performed seamlessly. We apply this method to Norwegian dairy farm data to estimate both unconstrained and constrained parametric and nonparametric models

An Empirical Comparison of Information-Theoretic Criteria in Estimating the Number of Independent Components of fMRI Data

BACKGROUND: Independent Component Analysis (ICA) has been widely applied to the analysis of fMRI data. Accurate estimation of the number of independent components of fMRI data is critical to reduce over/under fitting. Although various methods based on Information Theoretic Criteria (ITC) have been used to estimate the intrinsic dimension of fMRI data, the relative performance of different ITC in the context of the ICA model hasn't been fully investigated, especially considering the properties of fMRI data. The present study explores and evaluates the performance of various ITC for the fMRI data with varied white noise levels, colored noise levels, temporal data sizes and spatial smoothness degrees. METHODOLOGY: Both simulated data and real fMRI data with varied Gaussian white noise levels, first-order auto-regressive (AR(1)) noise levels, temporal data sizes and spatial smoothness degrees were carried out to deeply explore and evaluate the performance of different traditional ITC. PRINCIPAL FINDINGS: Results indicate that the performance of ITCs depends on the noise level, temporal data size and spatial smoothness of fMRI data. 1) High white noise levels may lead to underestimation of all criteria and MDL/BIC has the severest underestimation at the higher Gaussian white noise level. 2) Colored noise may result in overestimation that can be intensified by the increase of AR(1) coefficient rather than the SD of AR(1) noise and MDL/BIC shows the least overestimation. 3) Larger temporal data size will be better for estimation for the model of white noise but tends to cause severer overestimation for the model of AR(1) noise. 4) Spatial smoothing will result in overestimation in both noise models. CONCLUSIONS: 1) None of ITC is perfect for all fMRI data due to its complicated noise structure. 2) If there is only white noise in data, AIC is preferred when the noise level is high and otherwise, Laplace approximation is a better choice. 3) When colored noise exists in data, MDL/BIC outperforms the other criteria

Climatic niche evolution in new world monkeys (Platyrrhini)

Despite considerable interest in recent years on species distribution modeling and phylogenetic niche conservatism, little is known about the way in which climatic niches change over evolutionary time. This knowledge is of major importance to understand the mechanisms underlying limits of species distributions, as well as to infer how different lineages might be affected by anthropogenic climate change. In this study we investigate the tempo and mode climatic niche evolution in New World monkeys (Platyrrhini). Climatic conditions found throughout the distribution of 140 primate species were investigated using a principal component analysis, which indicated that mean temperature (particularly during the winter) is the most important climatic correlate of platyrrhine geographical distributions, accounting for nearly half of the interspecific variation in climatic niches. The effects of precipitation were associated with the second principal component, particularly with respect to the dry season. When models of trait evolution were fit to scores on each of the principal component axes, significant phylogenetic signal was detected for PC1 scores, but not for PC2 scores. Interestingly, although all platyrrhine families occupied comparable regions of climatic space, some aotid species such as Aotus lemurinus, A. jorgehernandezi, and A. miconax show highly distinctive climatic niches associated with drier conditions (high PC2 scores). This shift might have been made possible by their nocturnal habits, which could serve as an exaptation that allow them to be less constrained by humidity during the night. These results underscore the usefulness of investigating explicitly the tempo and mode o

Providing both autologous and allogeneic hematopoietic stem cell transplants (HSCT) may have a stronger impact on the outcome of autologous HSCT in adult patients than activity levels or implementation of JACIE at Belgian transplant centres.

While performance since the introduction of the JACIE quality management system has been shown to be improved for allogeneic hematopoietic stem cell transplants (HSCT), impact on autologous-HSCT remains unclear in Europe. Our study on 2697 autologous-HSCT performed in adults in 17 Belgian centres (2007-2013) aims at comparing the adjusted 1 and 3-yr survival between the different centres & investigating the impact of 3 centre-related factors on performance (time between JACIE accreditation achievement by the centre and the considered transplant, centre activity volume and type of HSCT performed by centres: exclusively autologous vs both autologous & allogeneic). We showed a relatively homogeneous performance between Belgian centres before national completeness of JACIE implementation. The 3 centre-related factors had a significant impact on the 1-yr survival, while activity volume and type of HSCT impacted the 3-yr survival of autologous-HSCT patients in univariable analyses. Only activity volume (impact on 1-yr survival only) and type of HSCT (impact on 1 and 3-yr survivals) remained significant in multivariable analysis. This is explained by the strong relationship between these 3 variables. An extended transplantation experience, i.e., performing both auto & allo-HSCT, appears to be a newly informative quality indicator potentially conveying a multitude of underlying complex factors