TY - JOUR T1 - REGRESSION MODELS BY GRETL AND R STATISTICAL PACKAGES FOR DATA ANALYSIS IN MARINE GEOLOGY AU - Lemenkova, Polina PY - 2019 DA - June JF - Uluslararası Çevresel Eğilimler Dergisi JO - IJENT PB - Muhammed Kamil ÖDEN WT - DergiPark SN - 2602-4160 SP - 39 EP - 59 VL - 3 IS - 1 LA - en AB - Gretland R statistical libraries enables to perform data analysis usingvarious algorithms, modules and functions. In this study, thegeospatial analysis of example case study of Mariana Trench, adeep-sea hadal trench located in west Pacific Ocean, was performedusing multi-functional combined approach of both Gretl and Rlibraries. The study aim was to model and visualize trends invariations of the trench’s properties: bathymetry (depths),geomorphology (steepness gradient), geology, volcanism (igneousrocks). The workflow included following statistical methods computedand visualized in Gretl and R libraries: 1) descriptive statistics;2) box plots, normality analysis byquantile-quantile (QQ)plots; 3) local weighted polynomial regression model(loess),4) linear regression by several methods:weightedleast squares(WLS) regression,ordinary least squares(OLS) regression,maximal likelihood linear regression and heteroskedasticityregression model; 5) confidence ellipses and marginal intervals fordata distribution; 6) robust estimation by Nadaraya–Watson kernelregression fit; 7) correlation analysis and matrix. The resultsinclude following ones. First, the geology of the trench has acorrelation with a slope angle gradient and igneous rocks (volcanismeffect). Second, the sedimentation is distributed unequally bytectonic plates. Third, there is a correlation between the slopegradient and aspect degree. 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