Beyond the Border - Kernel Density Estimation for Urban Geography

The kernelSmoothing() function allows you to square and smooth geolocated data. It calculates a classical kernel smoothing (conservative) or a geographically weighted median. There are four major call modes of the function. The first call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth) for a classical kernel smoothing and automatic grid. The second call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, quantiles) for a geographically weighted median and automatic grid. The third call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, centroids) for a classical kernel smoothing and user grid. The fourth call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, quantiles, centroids) for a geographically weighted median and user grid. Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon & al., in Computers, Environment and Urban Systems C.Brunsdon & al. (2002) , Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) .

Publication Toolkit for Water, Sanitation and Hygiene (WASH) Data

A toolkit to set up an R data package in a consistent structure. Automates tasks like tidy data export, data dictionary documentation, README and website creation, and citation management.

Keyboard Shortcuts for 'shiny'

Assign and listen to keyboard shortcuts in 'shiny' using the 'Mousetrap' Javascript library.

Find, Characterize, and Explore Extreme Events in Climate Projections

Inputs a directory of climate projection files and, for each, identifies and characterizes heat waves for specified study locations. The definition used to identify heat waves can be customized. Heat wave characterizations include several metrics of heat wave length, intensity, and timing in the year. The heat waves that are identified can be explored using a function to apply user-created functions across all generated heat wave files.This work was supported in part by grants from the National Institute of Environmental Health Sciences (R00ES022631), the National Science Foundation (1331399), and the Colorado State University Vice President for Research.

Send Email Messages

A light, simple tool for sending emails with minimal dependencies.

Structural Equation Modeling and Twin Modeling in R

Quickly create, run, and report structural equation models, and twin models. See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS. Timothy C. Bates, Michael C. Neale, Hermine H. Maes, (2019). umx: A library for Structural Equation and Twin Modelling in R. Twin Research and Human Genetics, 22, 27-41. .

Get XKCD Comic Data

Download data from individual XKCD comics, written by Randall Munroe < https://xkcd.com/>.

Spatial Temporal Analysis of Moving Polygons

Perform spatial temporal analysis of moving polygons; a longstanding analysis problem in Geographic Information Systems. Facilitates directional analysis, distance analysis, and some other simple functionality for examining spatial-temporal patterns of moving polygons.

Automatic Fixed Rank Kriging

Automatic fixed rank kriging for (irregularly located) spatial data using a class of basis functions with multi-resolution features and ordered in terms of their resolutions. The model parameters are estimated by maximum likelihood (ML) and the number of basis functions is determined by Akaike's information criterion (AIC). For spatial data with either one realization or independent replicates, the ML estimates and AIC are efficiently computed using their closed-form expressions when no missing value occurs. Details regarding the basis function construction, parameter estimation, and AIC calculation can be found in Tzeng and Huang (2018) . For data with missing values, the ML estimates are obtained using the expectation- maximization algorithm. Apart from the number of basis functions, there are no other tuning parameters, making the method fully automatic. Users can also include a stationary structure in the spatial covariance, which utilizes 'LatticeKrig' package.

Weighted Portmanteau Tests for Time Series Goodness-of-Fit

An implementation of the Weighted Portmanteau Tests described in "New Weighted Portmanteau Statistics for Time Series Goodness-of-Fit Testing" published by the Journal of the American Statistical Association, Volume 107, Issue 498, pages 777-787, 2012.