Search results for " regression [Classificació AMS]"
showing 10 items of 162 documents
Predicting Earthquake-Induced Landslides by Using a Stochastic Modeling Approach: A Case Study of the 2001 El Salvador Coseismic Landslides
2023
In January and February 2001, El Salvador was hit by two strong earthquakes that triggered thousands of landslides, causing 1259 fatalities and extensive damage. The analysis of aerial and SPOT-4 satellite images allowed us to map 6491 coseismic landslides, mainly debris slides and flows that occurred in volcanic epiclastites and pyroclastites. Four different multivariate adaptive regression splines (MARS) models were produced using different predictors and landslide inventories which contain slope failures triggered by an extreme rainfall event in 2009 and those induced by the earthquakes of 2001. In a predictive analysis, three validation scenarios were employed: the first and the second …
Wiener-Granger Causality in Network Physiology with Applications to Cardiovascular Control and Neuroscience
2016
Since the operative definition given by C. W. J. Granger of an idea expressed by N. Wiener, the Wiener–Granger causality (WGC) has been one of the most relevant concepts exploited by modern time series analysis. Indeed, in networks formed by multiple components, working according to the notion of segregation and interacting with each other according to the principle of integration, inferring causality has opened a window on the effective connectivity of the network and has linked experimental evidences to functions and mechanisms. This tutorial reviews predictability improvement, information-based and frequency domain methods for inferring WGC among physiological processes from multivariate…
Public-private sector pay gaps in Finland: A quantile regression analysis
2011
This paper examines public-private sector wage differentials in Finland using a quantile regression method. We control for the endogeneity of the working sector and allow the returns of individual skills to vary between industries. The results suggest that men earn a premium of 3 percent in the public sector at the lower-end jobs. At the median and the upper end of the distribution, men’s pay gap is negative, varying between 5 and 10 percent. Women, in turn, always earn more in the public sector (4–10 percent), and the premium is highest at the upper end of the earnings distribution. (JEL: J31, J45) peerReviewed
Measuring the gender wage gap : a methodological note
2020
We propose to estimate the Blinder-Oaxaca decomposition by a single-equation model augmented with interactions between the group membership and other predictors. The relative importance of predictors on the discriminatory wage gap is examined by the interaction coefficients, which may lead to very different conclusions than the usual percentage calculations using the detailed decomposition method. Comparisons are made between the traditional interpretations and those suggested here using wage data from Finland. The decomposition analysis suggests that the discriminatory male-female wage gap is largely related to work experience, while our preferred model points to the importance of family g…
Principals’ views on changes in the provision of support for learning and schooling in Finland after educational reform
2019
Recently, the large-scale reforms of special education have been carried out in many countries. This study focuses on the latest Finnish reform of special education in compulsory education. As principals lead educational reforms in schools, their role in the implementation of reform is significant. The study explores principals’ views on the changes in support arrangements after the educational reform. We used latent class analysis to identify the subgroups of principals who share similar views. In addition, we examined the relationship between the subgroups and individual, school, and municipal level factors using multinomial logistic regression analysis. Four subgroups were identified: im…
Application of selected methods of black box for modelling the settleability process in wastewater treatment plant
2017
The paper described how the results of measurement s of inflow wastewater temperature in the chamber, a degree of external and internal recirculation in the biological-mechanical wastewater treatment plan t (WWTP) in Cedzyna near Kielce, Poland, were used to make predictions of settleability of activated sludge. Three methods,namely: multivariate adaptive regression splines (MARS), random forests (RF) and modified random forests (RF+ SOM) were employed to compute activated sludge settleability. The results of analysis indicate that modified random forests demonstrate the best predictive abilities.
Interlinkages between operational conditions and direct and indirect greenhouse gas emissions in a moving bed membrane biofilm reactor
2016
Nitrous oxide (N2O) can be emitted during wastewater treatment contributing to the global warming due to its high global warming potential,. During the last ten years, several efforts have been provided to improve knowledge on: key mechanisms, operating factors and influent features affecting the N2O production/emission. However, the knowledge on the investigated issues is not completely mature. Indeed, in terms of mathematical modelling, literature shows that a reliable model has not yet been established due to the huge data set required and the complexity of the mechanistic models indicated as the most accurate. In this work, the first attempt to perform a multiregression analysis is pres…
Analysis of a database to predict the result of allergy testing in vivo in patients with chronic nasal symptoms.
2014
Background This article uses the logistic regression model for diagnostic decision making in patients with chronic nasal symptoms. We studied the ability of the logistic regression model, obtained by the evaluation of a database, to detect patients with positive allergy skin-prick test (SPT) and patients with negative SPT. The model developed was validated using the data set obtained from another medical institution. Methods The analysis was performed using a database obtained from a questionnaire administered to the patients with nasal symptoms containing personal data, clinical data, and results of allergy testing (SPT). All variables found to be significantly different between patients w…
Problem Transformation Methods with Distance-Based Learning for Multi-Target Regression
2020
Multi-target regression is a special subset of supervised machine learning problems. Problem transformation methods are used in the field to improve the performance of basic methods. The purpose of this article is to test the use of recently popularized distance-based methods, the minimal learning machine (MLM) and the extreme minimal learning machine (EMLM), in problem transformation. The main advantage of the full data variants of these methods is the lack of any meta-parameter. The experimental results for the MLM and EMLM show promising potential, emphasizing the utility of the problem transformation especially with the EMLM. peerReviewed
Estimating traffic operations at multi-lane roundabouts: A case study
2014
This paper addresses traffic modeling issues at urban multi-lane roundabouts where, despite circulating vehicles have priority, negotiation of the right-of-way can occur between antagonist traffic flows, as a result of minor drivers’ failing to obey the nominal operating rule (stop or yield control). Existing models for the estimation of operational performances have the shortcoming of not representing the interdependencies between entering and circulating vehicles at multi-lane roundabouts. An analytical capacity model derived from field observations was developed for this kind of intersections in a previous study. The complexity of the model lies in the difficulty of observing the behavio…