Search results for "Inference"
showing 10 items of 478 documents
Supervisor leadership style, employee regulatory focus, and leadership performance: A perspectivism approach
2019
[EN] Drawing on regulatory focus theory, this research proposes that transformational leadership performance depends on followers' circumstances. The analysis of 125 people from two Spanish service firms reveals that, apart from transformational leadership, the presence of academic education, intrinsic job satisfaction and high customer contact, and the absence of family responsibilities, are core conditions for the presence of high leadership performance. The first contribution of this study is the direct inference of follower's regulatory focus from the observation of individuals' circumstances. The second contribution is that leaders should consider followers' circumstances to adopt a su…
Off-line control of the postprandial glycemia in type 1 diabetes patients by a fuzzy logic decision support
2012
The target of this paper is to describe the use of fuzzy techniques in the development of a decision support system that allows the optimization of postprandial glycemia in type 1 diabetes patients taking into account the kind of meal taken by patients, the preprandial glycemia and the insulin resistance (the response of the body to insulin dose injection therapy). The decision support system can, in many cases, provide patients with the correct number of rapid insulin units that must be assumed to assure an optimal glycemic profile, keeping the blood glucose level close to the homeostatic condition, several hours after the meal.
Comparison between statistical and fuzzy approaches for improving diagnostic decision making in patients with chronic nasal symptoms
2014
This paper compares a fuzzy model, expressed in rule-form, with a well known statistical approach (i.e. logistic regression model) for diagnostic decision making in patients with chronic nasal symptoms. The analyses were carried out using a database obtained from a questionnaire administered to 1359 patients with nasal symptoms containing personal data, clinical data and skin prick test (SPT) results. Both the fuzzy model and the logistic regression model developed were validated using a data set obtained from another medical institution. The accuracy of the two models in identifying patients with positive or negative SPT was similar. This study is a preliminary step to the creation of a so…
Prostate Cancer Segmentation from Multiparametric MRI Based on Fuzzy Bayesian Model
2014
International audience
Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations.
2014
Abstract: Information-theory procedures are powerful tools for multimodel inference and are now standard methods in ecology. When performing model averaging on a given set of models, the importance of a predictor variable is commonly estimated by summing the weights of models where the variable appears, the so-called sum of weights (SW). However, SWs have received little methodological attention and are frequently misinterpreted. We assessed the reliability of SW by performing model selection and averaging on simulated data sets including variables strongly and weakly correlated to the response variable and a variable unrelated to the response. Our aim was to investigate how useful SWs are …
Smoothed score confidence interval for the breakpoint in segmented regression
2012
For the breakpoint parameter in segmented regression we consider confidence intervals based on the score statistic. Due to unsmoothness of the score, we propose to build the confidence intervals using its smoothed version under proper shape restrictions. Some simulations are presented to assess the finite sample performance of the proposed approach.
Testing for a breakpoint in segmented regression: a pseudo score approach
2011
To overcome the well known oddities in testing for the existence of a breakpoint in segmented regression models, we discuss a novel approach based on the Pearson X2 statistic which can be understood as an approximation of the Score statistic. We describe the method and present results from some simulations.
Los procesos inferenciales en lectores con síndrome de Down
2013
The aim of this work is to know if the source of the difficulty in making inferences, readers with Down syndrome, is in access to prior knowledge or constructing ideas from purely textual knowledge (based on Saldaña and Frith, 2002 for autism). Involved a sample of 20 students with Down syndrome and mild mental retardation (mean IQ = 60) and a control group of 20 children without cognitive deficits. They were matched as to their extent read metal age via Prueba de Evaluación del Retraso Lector (average 8 years). We created two experimental situations: a) subjects had to generate inferences based on physical knowledge, b) social inferences about knowledge. The ability to check and reaction t…
The Bayesian estimation of private investment in Finland
2009
Abstract This paper estimates an investment equation for private investment using Bayesian estimation techniques. In the paper we derive the optimal capital accumulation behavior in the model economy from the households’ optimization problem of utility. The equation is derived as in Smets and Wouters (2003). The model contains costly adjustment of investment and random shocks to adjustment cost function. The driving variable of investment is Tobin Q variable. The empirical proxy for Tobin Q in this paper is the ratio of OMX Helsinki Cap Index to the price index of the physical capital. The investment series is the seasonally adjusted private investment in quarterly national accounts. The AR…
Enhancing identification of causal effects by pruning
2018
Causal models communicate our assumptions about causes and effects in real-world phe- nomena. Often the interest lies in the identification of the effect of an action which means deriving an expression from the observed probability distribution for the interventional distribution resulting from the action. In many cases an identifiability algorithm may return a complicated expression that contains variables that are in fact unnecessary. In practice this can lead to additional computational burden and increased bias or inefficiency of estimates when dealing with measurement error or missing data. We present graphical criteria to detect variables which are redundant in identifying causal effe…