Search results for "Bootstrapping"
showing 10 items of 20 documents
The effects of data collection and observation methods on uncertainty of social networks in wild primates
2020
International audience; In social species, network centralities of group members shape social transmission and other social phenomena. Different factors have been found to influence the measurement of social networks, such as data collection and observation methods. In this study, we collected data on adults and juveniles and examined the effect of data collection method (ad libitum sampling vs. focal animal sampling) and observation method (interaction—grooming; play—vs. association—arm‐length; 2 m; 5 m proximities—) on social networks in wild vervet monkeys. First, we showed using a bootstrapping method, that uncertainty of ad libitum grooming and play matrices were lesser than uncertaint…
Optimal Cut Points for Remission and Response for the German Version of the Social Phobia Anxiety Inventory (SPAI).
2018
The German version of the Social Phobia and Anxiety Inventory (SPAI-G) is a validated measure for the detection of social anxiety disorder (SAD). The aim of the present study was to develop optimal cut points (OC) for remission and response to treatment for the SPAI-G.We used Receiver Operating Characteristic methods and bootstrapping to analyse the data of 359 patients after psychotherapeutic treatment. OCs where defined as the cut points with the highest sensitivity and specificity after bootstrapping.For remission, an OC of 2.79 was found, and for response, a change in score from pre- to posttreatment by 11% yielded best results.The OC we identified for remissionmay be used to improve th…
Model Transformation Languages and Their Implementation by Bootstrapping Method
2008
In this paper a sequence of model transformation languages L0, L1, L2 is defined. The first language L0 is very simple, and for this language it is easy to build an efficient compiler to C++. The next language L1 is an extension of L0, and it contains powerful pattern definition facilities. The last language L2 is of sufficiently high level and can be used for implementation of traditional pattern-based high level model transformation languages, as well as for the development of model transformations directly. For languages L1 and L2 efficient compilers have been built using the bootstrapping method: L1 to L0 in L0, and L2 to L1 in L1. The results confirm the efficiency of model transformat…
CONSTRUCTING, BOOTSTRAPPING, AND COMPARING MORPHOMETRIC AND PHYLOGENETIC TREES: A CASE STUDY OF NEW WORLD MONKEYS (PLATYRRHINI, PRIMATES)
2005
Morphometric data sets are often phenetically analyzed by using various kinds of spatial, metric, or nonmetric multivariate analyses. Such methods produce results that are difficult to compare directly with molecular or morphological phylogenetic hypotheses, which are usually expressed by using nonspatial tree representations. Therefore, it is useful in a comparative approach to analyze, and above all to visualize, morphometric pairwise relationships as tree structures. For this purpose, several additive or ultrametric methods exist, which often return different topologies for the same data set. Objective criteria are thus needed to identify the tree-building algorithm (or algorithm family)…
Entrepreneurial innovativeness and growth ambitions in thick vs. thin regional innovation systems
2018
Research in economic geography has paid increasing attention to regional innovation systems (RISs) as a potential vehicle for growth and development. Yet despite an increasing amount of research st...
Assessing the efficiency of wastewater treatment plants: A double-bootstrap approach
2017
Abstract Benchmarking the performance of wastewater treatment plants (WWTPs) is essential for promoting their long-term sustainability. Recent research has applied data envelopment analysis (DEA) models to evaluate the efficiency of WWTPs providing a synthetic index of their performance. However, the traditional DEA is a deterministic method; therefore, regression analysis cannot be used to explore the external factors influencing efficiency scores. To overcome this limitation, in this study, a double bootstrap DEA model was used for the first time to compute the efficiency scores for a sample of WWTPs. The confidence intervals for efficiency scores were estimated for each facility. Results…
Non-parametric probabilistic forecasting of academic performance in Spanish high school using an epidemiological modelling approach
2013
Academic underachievement is a concern of paramount importance in Europe, and particularly in Spain, where around of 30% of the students in the last two courses in high school do not achieve the minimum knowledge academic requirement. In order to analyse this problem, we propose a mathematical model via a system of ordinary differential equations to study the dynamics of the academic performance in Spain. Our approach is based on the idea that both, good and bad study habits, are a mixture of personal decisions and influence of classmates. Moreover, in order to consider the uncertainty in the estimation of model parameters, a bootstrapping approach is employed. This technique permits to for…
Bootstrapping profit change: An application to Spanish banks
2012
The aim of this study is to provide a tool which enables us to conduct statistical analysis in the context of changes in productivity and profit. We build on previous initiatives to decompose profit change into mutually exclusive and exhaustive sources. To do this we use distance functions, which are calculated empirically using linear programming techniques. However, we may not learn a great deal by solving these linear programs unless methods of statistical analysis are used to examine the properties of the relevant estimators. Our purpose is to provide a methodology based on bootstrap that allows us to conduct statistical inference for the profit change decomposition. Thus, it will be po…
Explainable Reinforcement Learning with the Tsetlin Machine
2021
The Tsetlin Machine is a recent supervised machine learning algorithm that has obtained competitive results in several benchmarks, both in terms of accuracy and resource usage. It has been used for convolution, classification, and regression, producing interpretable rules. In this paper, we introduce the first framework for reinforcement learning based on the Tsetlin Machine. We combined the value iteration algorithm with the regression Tsetlin Machine, as the value function approximator, to investigate the feasibility of training the Tsetlin Machine through bootstrapping. Moreover, we document robustness and accuracy of learning on several instances of the grid-world problem.
Lexical and grammatical development in children at family risk of dyslexia from early childhood to school entry: a cross-lagged analysis.
2019
AbstractThe aim of this study was to examine (a) the development of vocabulary and grammar in children with family-risk (FR) of dyslexia and their peers with no such risk (NoFR) between ages 1;6 and 6;0, and (b) whether FR-status exerted an effect on the direction of temporal relationships between these two constructs. Groups were assessed at seven time-points using standardised tests and parental reports. Results indicated that although FR and NoFR children had a similar development in the earlier years, the FR group appeared to perform significantly more poorly on vocabulary at the end of the preschool period. Results showed no significant effect of FR status on the cross-lagged relations…