Search results for "Lasso"
showing 10 items of 110 documents
Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs
2014
We develop an algorithm that incorporates network information into regression settings. It simultaneously estimates the covariate coefficients and the signs of the network connections (i.e. whether the connections are of an activating or of a repressing type). For the coefficient estimation steps an additional penalty is set on top of the lasso penalty, similarly to Li and Li (2008). We develop a fast implementation for the new method based on coordinate descent. Furthermore, we show how the new methods can be applied to time-to-event data. The new method yields good results in simulation studies concerning sensitivity and specificity of non-zero covariate coefficients, estimation of networ…
Influenza della temperatura di pirolisi e del tempo di residenza sulle proprietà fisico-chimiche del biochar prodotto da pollina
2013
La pollina è tradizionalmente utilizzata in agricoltura come fertilizzante organico grazie al suo alto contenuto in nutrienti immediatamente disponibili per le piante (principalmente azoto, potassio e fosforo). Nonostante i vantaggi apportati alle colture, l’eccessivo uso della pollina come ammendante del suolo può causare gravi problemi ambientali, tra cui rischi per la salute umana e lisciviazione di nitrati o altri inquinanti nelle acquee sotterranee. Per diminuire i rischi legati al suo utilizzo, una soluzione alternativa potrebbe essere il ri-utilizzo energetico della pollina tramite la sua conversione in biochar. Il biochar è una sostanza carboniosa derivante dalla pirolisi di qualsia…
Lielas dimensijas vektorautoregresīvo modeļu izmantošana prognozēšanai
2016
Vektorautoregresīvā procesa (VAR) modeļi ir parādījuši sevi, kā efektīva metode makroekonomisko laikrindu prognozēšanai. Taču VAR trūkums ir tāds, ka modeļa parametru telpa pieaug kvadrātiski, pievienojot modelim jaunu mainīgo. Tā kā mūsdienās valstu ekonomikas paliek savstarpēji saistītas, paliek aktuālāks jautājums par to, kā modelī iekļaut nemodelējamus ekzogēnos mainīgos. Vektorautoregresīvā procesa modelis ar ekzogēniem mainīgajiem (VAR-X ) ļauj iekļaut nemodelējamus mainīgos, taču tāpat sastopas ar dimensionalitātes problēmu. Lai uzlabotu retāka periodiskuma daudzdimensiju datu prognozēšanu, šajā darbā teorētiski izpētam regularizitētos VAR un VAR-X modeļus, kas izretina parametru tel…
Isolation, identification and metabolic characterization of hydrocarbonoclastic bacteria from a polluted harbour in Sicily (Italy)
2014
The petrochemical site of Priolo-Augusta-Melilli (Sicily, Italy), is a Site of National Interest (SIN) due to high levels of environmental contamination of the coastline and a specific "national program of environmental remediation and restoration" was developed in order to allow remediation and restoration of contaminated sites. In order to identify the key hydrocarbon degraders and explore the natural bioremediation potential of the contaminated area, a total of six sediment and sea water cores were collected inside the Priolo Harbour (SR, Italy). After biological (bacterial counts, PCR-DGGE) and chemical-physical characterization (quali-, quantitative measures of hydrocarbons and heavy m…
Induced smoothing in LASSO regression
The thesis is being carried out with the National research Council at the Institute of Biomedicine and Molecular Immunology "Alberto Monroy" of Palermo, where I am a fellow, under the supervision of MD Stefania La Grutta. Our research unit is focused on clinical research in allergic respiratory problems in children. In particular, we are interested in to assess the determinants of impaired lung function in a sample of outpatient asthmatic children aged between 5 and 17 years enrolled from 2011 to 2017. Our dataset is composed by n = 529 children and several covariates regarding host and environmental factors. This thesis focuses on hypothesis testing in lasso regression, when one is interes…
OCTA atlīdzību apjoma modelēšana, lietojot vispārināto lineāro modeli
2017
Darbs veltīts obligātās civiltiesiskās transportlīdzekļu apdrošināšanas (OCTA) atlīdzību modelēšanai. Modeļu klase, ko izvēlēts lietot, ir vispārinātais lineārais modelis (GLM), kas praksē tiek bieži lietots apdrošināšanas atlīdzību modelēšanai. Darbā aprakstīti vispārinātā lineārā modeļa teorijas pamati un modeļa precizitātes novērtēšanas mēri. Aplūkotas dažādas modeļa parametru novērtēšanas un faktoru atlases metodes, no iegūtajiem modeļiem izvēlēts modelis ar labāko pielāgošanas kvalitāti un precīzāko prognozēšanas spēju. Visbiežāk lietotās metodes - iteratīvā mazāko kvadrātu metode parametru novērtēšanai un soļu regresija faktoru atlasei tika salīdzinātas ar lasso un elastīgo tīklu regu…
Variable selection with unbiased estimation: the CDF penalty
2022
We propose a new SCAD-type penalty in general regression models. The new penalty can be considered a competitor of the LASSO, SCAD or MCP penalties, as it guarantees sparse variable selection, i.e., null regression coefficient estimates, while attenuating bias for the non-null estimates. In this work, the method is discussed, and some comparisons are presented.
Biodegradation Potential of Oil-degrading Bacteria Related to the Genus Thalassospira Isolated from Polluted Coastal Area in Mediterranean Sea
2021
Three bacterial species related to the genus Thalassospira (T. lucentensis, T. xianhensis and T. profundimaris), isolated from polluted sediment and seawater samples collected from Priolo Bay (eastern coast of Sicily, Ionian Sea), were analyzed for their biotechnological potential. For this purpose, the presence of specific catabolic genes associated to aliphatic and aromatic hydrocarbon metabolism, the production of biosurfactants and emulsification activity, the capability to degrade oil-derived linear, branched, cyclic alkanes, and polycyclic aromatic hydrocarbons (PAHs) were evaluated. Alkane hydroxylase gene (alkano-monoxygenase alkb and citocrome P450) were present in genome of all st…
The Joint Censored Gaussian Graphical Lasso Model
2022
The Gaussian graphical model is one of the most used tools for inferring genetic networks. Nowadays, the data are often collected from different sources or under different biological conditions, resulting in heterogeneous datasets that exhibit a dependency structure that varies across groups. The complex structure of these data is typically recovered using regularized inferential procedures that use two penalties, one that encourages sparsity within each graph and the other that encourages common structures among the different groups. To this date, these approaches have not been developed for handling the case of censored data. However, these data are often generated by gene expression tech…
LASSO regression via smooth L1-norm approximation
2010
This paper discusses estimation of regression model with LASSO penalty when the L1-norm is replaced with its parametric smooth approximation. The resulting parameter estimators are more manageable than those from standard LASSO, standard errors are easy computed via a sandwich formula, and the model degrees of freedom may be computed straightforwardly. Moreover the resulting objective function may be minimized using usual optimization algorithms for regular models, for instance Newton-Raphson or iterative least squares.