Showing 5 of total 5 results (show query)
rspatial
terra:Spatial Data Analysis
Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).
Maintained by Robert J. Hijmans. Last updated 14 hours ago.
geospatialrasterspatialvectoronetbbprojgdalgeoscpp
560 stars 17.65 score 17k scripts 856 dependentsdaattali
shinyjs:Easily Improve the User Experience of Your Shiny Apps in Seconds
Perform common useful JavaScript operations in Shiny apps that will greatly improve your apps without having to know any JavaScript. Examples include: hiding an element, disabling an input, resetting an input back to its original value, delaying code execution by a few seconds, and many more useful functions for both the end user and the developer. 'shinyjs' can also be used to easily call your own custom JavaScript functions from R.
Maintained by Dean Attali. Last updated 7 months ago.
740 stars 17.28 score 8.9k scripts 400 dependentsrspatial
raster:Geographic Data Analysis and Modeling
Reading, writing, manipulating, analyzing and modeling of spatial data. This package has been superseded by the "terra" package <https://CRAN.R-project.org/package=terra>.
Maintained by Robert J. Hijmans. Last updated 2 days ago.
163 stars 17.23 score 58k scripts 562 dependentskkholst
lava:Latent Variable Models
A general implementation of Structural Equation Models with latent variables (MLE, 2SLS, and composite likelihood estimators) with both continuous, censored, and ordinal outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>). Mixture latent variable models and non-linear latent variable models (Holst and Budtz-Joergensen (2020) <doi:10.1093/biostatistics/kxy082>). The package also provides methods for graph exploration (d-separation, back-door criterion), simulation of general non-linear latent variable models, and estimation of influence functions for a broad range of statistical models.
Maintained by Klaus K. Holst. Last updated 3 months ago.
latent-variable-modelssimulationstatisticsstructural-equation-models
33 stars 12.87 score 610 scripts 478 dependentstill-tietz
parsel:Parallel Dynamic Web-Scraping Using 'RSelenium'
A system to increase the efficiency of dynamic web-scraping with 'RSelenium' by leveraging parallel processing. You provide a function wrapper for your 'RSelenium' scraping routine with a set of inputs, and 'parsel' runs it in several browser instances. Chunked input processing as well as error catching and logging ensures seamless execution and minimal data loss, even when unforeseen 'RSelenium' errors occur. You can additionally build safe scraping functions with minimal coding by utilizing constructor functions that act as wrappers around 'RSelenium' methods.
Maintained by Till Tietz. Last updated 1 years ago.
15 stars 3.88 score 8 scripts