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An official USGS software project is code reviewed and approved at the bureau-level for distribution.

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Simulation and comparison of five estimators of variability in units of standard deviation for small samples drawn from normally distributed data

It is convenient to measure or estimate variation in samples or distributions in units of standard deviations. There are alternative methods of estimation of standard deviation aside from the conventional and well-known definition. Estimation of standard deviation for very small samples (as small as two), whereas not always ideal, might be useful in certain practical circumstances. A simulation st

Study of L-kurtosis and several distribution families for prediction of uncertainty distributions, An applied software technical note concerning L-kurtosis use in daily salinity prediction from multiple machine learning methods

Statistical predictions that are based on multiple machine learning (MML) methods (from including differing training regimes) produce differing predictions. When the predictions are combined to a final estimate, then there are residuals of the predictions spread around the final estimate. It is common to assume normality or near-normality of the residuals (errors), but the assumption of normality

Comparing datasets by surveillance method using spatial models

This software compares statistical methods to model habitat risk of CWD in white-tailed deer in Pennsylvania using Bayesian hierarchical models in R-INLA and compares these results with model output from WinBugs. The software also uses R-INLA with the Stochastic Partial Differential Approach (SPDE) to compare different surveillance methods to model CWD in relation to habitat features and age and s

Code to Support Hypoxia vulnerability in the salmon watersheds of Southeast Alaska

Oxygen depletion events (hypoxia) in coastal aquatic ecosystems occur more frequently, yet their causes and consequences remain poorly understood. We identified key drivers of hypoxia in Southeast Alaska watersheds for long-term hypoxia monitoring. This software release contains one R script that can be used to calculate hypoxia risk from environmental variables. This R code will re-create Figure

Application of Spatially Misaligned Regression Model to Assess Impacts of White-Nose Syndrome

Code release for a statistical framework that provides a solution to overcome institutionally siloed monitoring activities in order to inform species conservation across large landscapes. Stan code and documentation to provide access and adaptation for other wildlife disease applications.

GRAPES.jl - GRAph Prediction of Earthquake Shaking in Julia (Version 1.0.0)

GRAPES.jl is a Julia-language code for earthquake early warning. GRAPES.jl implements the GRAph Prediction of Earthquake Shaking (GRAPES) algorithm using graph neural networks. The GRAPES.jl package provides code for EEW ground motion predictions.

DGMETA (Version 1): Dissolved Gas Modeling and Environmental Tracer Analysis Computer Program

DGMETA (Dissolved Gas Modeling and Environmental Tracer Analysis) is a Microsoft Excel-based computer program that is used for modeling air-water equilibrium conditions from measurements of dissolved gases and for computing concentrations of environmental tracers that rely on air-water equilibrium model results. DGMETA can solve for the temperature, salinity, excess air, fractionation of gases, or

REDPy - Repeating Earthquake Detector in Python (Version 1.0.0)

REDPy (Repeating Earthquake Detector in Python) is a tool for automated detection and analysis of repeating earthquakes in continuous data. It works without any previous assumptions of what repeating seismicity looks like (that is, does not require a template event). Repeating earthquakes are clustered into families based on waveform similarity via cross-correlation across multiple stations. All d

Population Viability Model for Western Pond Turtle

The code herein uses a triple loop structure to simulate a spatially implicit stage structured matrix model for two species of western pond turtle with parametric uncertainty and temporal stochasticity.

digger: A python package for D-Claw model inputs

Digger is a python package that provides a number of pre- and post-processing tools for working with the D-Claw model.

R code for calculating imperilment of freshwater fish with a Bayesian belief network

This R script is reproduces a Bayesian belief network built within the propriety software program, Netica. The R- and Netica-based belief networks were used in Dunn and Schumann et al. (in press), which presents an approach for calculating imperilment of freshwater fishes.


The goal of algaeClassify is to facilitate the analysis of taxonomic and functional trait data for phytoplankton.