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Thomas Pingel's Projects

bidimensional-regression-matlab icon bidimensional-regression-matlab

Bidimensional regression is a technique to measure the agreement between two, two-dimensional vectors. R-square provides a single value of overall agreement, while scale, translation, and rotation information is also provided. This function has been validated against Friedman and Kohler's provided sample dataset.

cohens-kappa-matlab icon cohens-kappa-matlab

This is a simple implementation of Cohen's Kappa statistic, which measures agreement for two judges for values on a nominal scale. See the Wikipedia entry for a quick overview, or you can get the original article from Sage Publications. Kappa has been used extensively in psychology, and has been more recently applied to land cover / land use changes and to assessments of accuracy for classification algorithms in Remote Sensing (Congalton, 1991; Jensen, 2005).

geodata icon geodata

A collection of simple geodata, primarily for teaching.

geog_493_notebooks icon geog_493_notebooks

Notebooks for Northern Illinois University's GEOG 493 (Computer Programming for the Geographic and Atmospheric Sciences)

great-circle-distance-matlab icon great-circle-distance-matlab

Very simple implementation of a great circle distance calculator, assuming a spherical Earth. It isn't, by the way. You should use: d = distance(lon1, lat1, lon2, lat2, almanac('earth', 'wgs84')); if you have the Mapping Toolbox.

lcpy icon lcpy

least cost path modeling

lio-sam icon lio-sam

LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

loam icon loam

Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.

loam_livox icon loam_livox

A robust LiDAR Odometry and Mapping (LOAM) package for Livox-LiDAR

loam_velodyne-1 icon loam_velodyne-1

Laser Odometry And Mapping (LOAM) SLAM ROS package for 3D Velodyne VLP-16 laser scanner

mackskill-matlab icon mackskill-matlab

Nonparametric Two-way ANOVA Used For Block Designs with Unequal Numbers of Multiple Observations

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