rvalavi Goto Github PK

aec

Introduction to Spatial Analysis with R - Advanced Environmental Computation Course

aws-spatial

Design and provision AWS infrastructure for analysing big geospatial data

blockcv

The blockCV package creates spatially or environmentally separated training and testing folds for cross-validation to provide a robust error estimation in spatially structured environments. See

computer-systems-cs-app3e

My solutions of Computer Systems: A Programmer’s Perspective, Third Edition (CS:APP3e) book, the text book for the course, CMU15-213: Introduction to Computer Systems.

disdat

Data for Evaluating Species Distribution Modelling Methods

ecolevol_r_workshop

ee_intro_spatial_workshop

Material from the Introduction to Spatial Analysis in R workshop from the Ecology and Evolution PhD Program. See here:

fastapi

FastAPI for Postgres DB

gdm

R package for Generalized Dissimilarity Modeling

geneticriskindex

geocompr

Forthcoming book on geographic data with R

ggresponse

Create response curve for different models in ggplot2.

kd-tree

An implementation of k-d tree for searching

lstmodelling

This repository is for the materials related to the manuscript for consideration in the GIScience & Remote Sensing Journal.

maxnet

An R package that implements much of the functionality of the Maxent Java application

myspatial

A collection of my functions for spatial data analysis and modelling in R

predicts

Methods for spatial prediction

presence-only-sdm

Predictive performance of presence-only species distribution models

ranger

A Fast Implementation of Random Forests

rann2

Fast Nearest Neighbour Search (Rcpp wrapper for libANN)

rmarkdown-action

Github action to render documents using rmarkdown. Includes pandoc and tinytex installations

sdm-spatial-validation

Appendix S1 for "Flexible species distribution modelling methods perform well on spatially separated testing data"

sdm_with_ppm

A tutorial for modelling species distributions with spatial point processes

sdm_with_python

Species distribution modelling in Python

sdmverse

sdmverse is a collaborative metapackage for listing all the metadata of the Species Distribution Modelling (SDM) packages. sdmverse includes a graphical interface available locally or online (see below). sdmverse integrates metadata from SDM packages and checks their validity against the CRAN metadata for perenity.

sdmwithrfs

Modelling species presence-only data with random forests

ubuntuplaybook

Ansible playbook for configuration of my ubuntu/pop-os!