Search results for " regression [Classificació AMS]"

showing 10 items of 162 documents

Exploring the effect of absence selection on landslide susceptibility models: A case study in Sicily, Italy

2016

Abstract A statistical approach was employed to model the spatial distribution of rainfall-triggered landslides in two areas in Sicily (Italy) that occurred during the winter of 2004–2005. The investigated areas are located within the Belice River basin and extend for 38.5 and 10.3 km 2 , respectively. A landslide inventory was established for both areas using two Google Earth images taken on October 25th 2004 and on March 18th 2005, to map slope failures activated or reactivated during this interval. Geographic Information Systems (GIS) were used to prepare 5 m grids of the dependent variables (absence/presence of landslide) and independent variables (lithology and 13 DEM-derivatives). Mul…

Multivariate Adaptive Regression Splines (MARS)Geographic information system010504 meteorology & atmospheric sciencesCalibration (statistics)Lithologymedia_common.quotation_subjectSettore GEO/04 - Geografia Fisica E GeomorfologiaGeographic Information Systems (GIS)010502 geochemistry & geophysicsSpatial distribution01 natural sciencesSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliGeographic Information Systems (GIS); Google Earth; Landslide susceptibility; Multivariate Adaptive Regression Splines (MARS); Earth-Surface Processes0105 earth and related environmental sciencesmedia_commonEarth-Surface ProcessesVariablesMultivariate adaptive regression splinesReceiver operating characteristicbusiness.industryGoogle EarthLandslideLandslide susceptibilitybusinessCartographyGeology
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Mapping Susceptibility to Debris Flows Triggered by Tropical Storms: A Case Study of the San Vicente Volcano Area (El Salvador, CA)

2021

In this study, an inventory of storm-triggered debris flows performed in the area of the San Vicente volcano (El Salvador, CA) was used to calibrate predictive models and prepare a landslide susceptibility map. The storm event struck the area in November 2009 as the result of the simultaneous action of low-pressure system 96E and Hurricane Ida. Multivariate Adaptive Regression Splines (MARS) was employed to model the relationships between a set of environmental variables and the locations of the debris flows. Validation of the models was performed by splitting 100 random samples of event and non-event 10 m pixels into training and test subsets. The validation results revealed an excellent (…

Multivariate Adaptive Regression Splines (MARS)Multivariate adaptive regression splineslow-pressure system 96EReceiver operating characteristicSettore GEO/04 - Geografia Fisica E GeomorfologiaStormLandslideMars Exploration ProgramDebrisDebris flowdebris flowsSan Vicente volcanodebris flowEl Salvadorlandslide susceptibilitytropical storm IdaTropical cycloneGeomorphologyGeologyEarth
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Prediction of debris-avalanches and -flows triggered by a tropical storm by using a stochastic approach: An application to the events occurred in Moc…

2019

Abstract Landslides are among the most dangerous natural processes. Debris avalanches and debris flows in particular have often caused casualties and severe damage to infrastructures in a wide range of environments. The assessment of susceptibility to these phenomena may help policy makers in mitigating the associated risk and thus it has attracted special attention in the last decades. In this experiment, we assessed susceptibility to debris-avalanche and -flow landslides by using a stochastic approach. Two different modeling techniques were employed: i) Multivariate Adaptive Regression Splines (MARS) and ii) Logistic Regression (LR). Both MARS and LR allow for calculating the probability …

Multivariate Adaptive Regression Splines (MARS)Topographic Wetness IndexMultivariate adaptive regression splinesTropical storm010504 meteorology & atmospheric sciencesElevationLogistic regression (LR)Mocoa (Colombia)TerrainLandslideMars Exploration ProgramDebris flowLandslide susceptibility010502 geochemistry & geophysics01 natural sciencesDebrisRange (statistics)CartographyGeology0105 earth and related environmental sciencesEarth-Surface ProcessesGeomorphology
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Evaluation of debris flow susceptibility in El Salvador (CA): a comparison between Multivariate Adaptive Regression Splines (MARS) and Binary Logisti…

2018

In the studies of landslide susceptibility assessment, which have been developed in recent years, statistical methods have increasingly been applied. Among all, the BLR (Binary Logistic Regression) certainly finds a more extensive application while MARS (Multivariate Adaptive Regression Splines), despite the good performance and the innovation of the strategies of analysis, only recently began to be employed as a statistical tool for predicting landslide occurrence. The purpose of this research was to evaluate the predictive performance and identify possible drawbacks of the two statistical techniques mentioned above, focusing in particular on the prediction of debris flows. To this aim, an…

Multivariate Adaptive Regression Splines (MARS)hurricane IdaMultivariate adaptive regression splines010504 meteorology & atmospheric sciencesSettore GEO/04 - Geografia Fisica E GeomorfologiaBinary Logistic Regression (BLR)0208 environmental biotechnologyGeography Planning and Developmentlcsh:G1-92202 engineering and technologyMars Exploration ProgramDebris flowLogistic regression01 natural sciences020801 environmental engineeringDebris flowdebris flowsStatisticsEl SalvadorGeneral Earth and Planetary Scienceslandslide susceptibilitySettore GEO/05 - Geologia Applicatalcsh:Geography (General)Geology0105 earth and related environmental sciencesHungarian Geographical Bulletin
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Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice Riv…

2015

Abstract In this paper, terrain susceptibility to earth-flow occurrence was evaluated by using geographic information systems (GIS) and two statistical methods: Logistic regression (LR) and multivariate adaptive regression splines (MARS). LR has been already demonstrated to provide reliable predictions of earth-flow occurrence, whereas MARS, as far as we know, has never been used to generate earth-flow susceptibility models. The experiment was carried out in a basin of western Sicily (Italy), which extends for 51 km 2 and is severely affected by earth-flows. In total, we mapped 1376 earth-flows, covering an area of 4.59 km 2 . To explore the effect of pre-failure topography on earth-flow sp…

Multivariate adaptive regression splinesGeographic information systembusiness.industryGeographic Information Systems (GIS)Logistic regressionStatistical modelLandslideTerrainEarth-flowOverfittingLogistic regressionLandslide susceptibilityMultivariate adaptive regression splineDigital elevation modelbusinessCartographyReceiver operating characteristic curveGeologyEarth-Surface Processes
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Structural invariants for the prediction of relative toxicities of polychloro dibenzo-p-dioxins and dibenzofurans

2004

Multivariate models are reported that can predict the relative toxicity of compounds with severe environmental impact, namely polychloro dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs). Multiple linear regression analysis (MLR) and partial least square projections of latent variables (PLS) show the usefulness of graph-theoretical descriptors, mainly topological charge indices (TCIs), in these series. The general trends of the group are correctly reproduced and better results are presented than have previously been published. In general, the more toxic compounds exhibit more symmetric molecular structures.

Multivariate statisticsCarcinoma HepatocellularPolychlorinated DibenzodioxinsRelative toxicityQuantitative Structure-Activity RelationshipLatent variableDioxinsCatalysisInorganic ChemistryToxicologyComputational chemistryDrug DiscoveryLinear regressionCytochrome P-450 CYP1A1AnimalsSoil PollutantsLeast-Squares AnalysisPhysical and Theoretical ChemistryMolecular BiologyBenzofuransModels StatisticalChemistryOrganic ChemistryReproducibility of Resultsfood and beveragesNeoplasms ExperimentalGeneral MedicineModels TheoreticalRatsDisease Models AnimalModels ChemicalDrug DesignMultivariate AnalysisLinear ModelsEnvironmental PollutantsMultiple linear regression analysisInformation SystemsMolecular Diversity
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Multivariate regression analysis applied to the calibration of equipment used in pig meat classification in Romania.

2016

This paper highlights the statistical methodology used in a dissection experiment carried out in Romania to calibrate and standardize two classification devices, OptiGrade PRO (OGP) and Fat-o-Meat'er (FOM). One hundred forty-five carcasses were measured using the two probes and dissected according to the European reference method. To derive prediction formulas for each device, multiple linear regression analysis was performed on the relationship between the reference lean meat percentage and the back fat and muscle thicknesses, using the ordinary least squares technique. The root mean squared error of prediction calculated using the leave-one-out cross validation met European Commission (EC…

Multivariate statisticsMeatMean squared errorFood HandlingSwine0211 other engineering and technologies02 engineering and technologyCross-validationStatisticsCalibrationMedicineAnimals021110 strategic defence & security studiesbusiness.industryBack fatRomania0402 animal and dairy scienceRegression analysis04 agricultural and veterinary sciences040201 dairy & animal scienceAdipose TissueOrdinary least squaresCalibrationBody CompositionMultiple linear regression analysisbusinessFood ScienceMeat science
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How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study

2019

Abstract This paper replicates the Diebold and Yilmaz (2012) study on the connectedness of the commodity market and three other financial markets: the stock market, the bond market, and the FX market, based on the Generalized Forecast Error Variance Decomposition, GEFVD. We show that the net spillover indices (of directional connectedness), used to assess the net contribution of one market to overall risk in the system, are sensitive to the normalization scheme applied to the GEFVD. We show that, considering data generating processes characterized by different degrees of persistence and covariance, a scalar-based normalization of the Generalized Forecast Error Variance Decomposition is pref…

Normalization (statistics)Economics and EconometricsSocial connectedness020209 energySettore SECS-P/05 - Econometria02 engineering and technologyNormalization schemeconnectednessSpillover effect0502 economics and business0202 electrical engineering electronic engineering information engineeringEconometrics050207 economicsMathematicsspillover normalization connectednessVector autoregression models05 social sciencesFinancial marketCovarianceCausalitySpilloverGeneral EnergynormalizationGeneralized forecast error variance decompositionCommodity price fluctuations Driving forces Nonparametric additive regression modelsVariance decomposition of forecast errorsBond marketStock marketSimulationNormalization schemes
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Effects of p63 expression on survival in oral squamous cell carcinoma

2007

BACKGROUND: P63 is the protein codified by p63 gene, a p53 gene homolog, known for its pivotal role in cell cycle regulation, and involved in the tumor differentiation. Aims of the present study were to assess the frequency and pattern of p63 protein expression in oral squamous cell carcinoma (OSCC) in relation to the main tumour characteristics and to verify whether p63 can be considered a marker of prognosis in patients with OSCC. MATERIAL AND METHODS: In a retrospective study, a cohort of 64 OSCC patients was investigated for p63 protein expression and its cellular localization by immunohistochemistry (monoclonal mouse anti-human p63 protein-clone 4A4). After grouping by p63 expression, …

OncologyAdultMaleCancer Researchmedicine.medical_specialtyPathologySurvival rateBiologyOSCCInternal medicinemedicineBiomarkers TumorCox regression analysisHumansGrading (tumors)GeneSurvival rateCellular localizationAgedNeoplasm StagingCox regression analysis; OSCC; p53 family; p63; Survival rate;p63integumentary systemTumor Suppressor ProteinsRetrospective cohort studyGeneral MedicineMiddle AgedPrognosisSurvival Analysisp63 p53 family OSCC Survival rate Cox regression analysisDNA-Binding Proteinsstomatognathic diseasesOncologyCohortMonoclonalCarcinoma Squamous CellTrans-ActivatorsImmunohistochemistryFemaleMouth NeoplasmsOSCCsense organsp53 familyp53 familyCox regressionTranscription Factors
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Effect of c-Met expression on survival in head and neck squamous cell carcinoma

2005

The proto-oncogene c-Met has been suggested to be associated with progression of squamous cell carcinoma of the head and neck. The aims of the present study were to assess the prevalence of c-Met expression in oral squamous cell carcinoma (OSCC) and to verify whether c-Met can be considered a marker of prognosis in these patients. In a retrospective study, a cohort of 84 OSCC patients was investigated for c-Met expression and its cellular localization by immunohistochemistry. After grouping for c-Met expression, OSCC patients were statistically analyzed for the variables age, gender, histological grading, tumor node metastasis, staging and overall survival rate. Univariate and multivariate …

OncologyAdultMalemedicine.medical_specialtyc-Met; Cox regression analysis; Oral squamous cell carcinoma;C-MetAdolescentcox regression analysisProto-Oncogene Maschemistry.chemical_compoundInternal medicinemedicineBiomarkers TumorHumansBasal cellHead and neckc-MetNeoplasm Stagingbusiness.industryMouth MucosaGeneral MedicineMiddle AgedProto-Oncogene Proteins c-metmedicine.diseasePrognosisHead and neck squamous-cell carcinomaImmunohistochemistryUp-Regulationoral squamous cell carcinomastomatognathic diseaseschemistryCarcinoma Squamous CellFemaleMouth Neoplasmsbusiness
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