This package is considered a duplicate. The official version of this package is found at:https://morrowcj.r-universe.dev/remotePARTS

Package: remotePARTS 1.0.4

Clay Morrow

remotePARTS: Spatiotemporal Autoregression Analyses for Large Data Sets

These tools were created to test map-scale hypotheses about trends in large remotely sensed data sets but any data with spatial and temporal variation can be analyzed. Tests are conducted using the PARTS method for analyzing spatially autocorrelated time series (Ives et al., 2021: <doi:10.1016/j.rse.2021.112678>). The method's unique approach can handle extremely large data sets that other spatiotemporal models cannot, while still appropriately accounting for spatial and temporal autocorrelation. This is done by partitioning the data into smaller chunks, analyzing chunks separately and then combining the separate analyses into a single, correlated test of the map-scale hypotheses.

Authors:Clay Morrow [aut, cre], Anthony Ives [aut]

remotePARTS_1.0.4.tar.gz
remotePARTS_1.0.4.zip(r-4.7-x86_64)remotePARTS_1.0.4.zip(r-4.7-arm64)remotePARTS_1.0.4.zip(r-4.6-x86_64)remotePARTS_1.0.4.zip(r-4.6-arm64)
remotePARTS_1.0.4.tar.gz(r-4.7-arm64)remotePARTS_1.0.4.tar.gz(r-4.7-x86_64)remotePARTS_1.0.4.tar.gz(r-4.6-arm64)remotePARTS_1.0.4.tar.gz(r-4.6-x86_64)
remotePARTS_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
remotePARTS/json (API)

# Install 'remotePARTS' in R:

install.packages('remotePARTS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/morrowcj/remoteparts/issues

Uses libs:

c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

ndvi_AK10000 - NDVI remote sensing data for 10,000 random pixels from Alaska, with rare land classes removed.
partGLS_ndviAK - Partitioned GLS results

On CRAN:

cpp openmp

3.15 score 28 scripts 291 downloads 20 exports 8 dependencies

Last updated from:aa1aa997c7. Checks:10 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	151
linux-devel-x86_64	OK	238
source / vignettes	OK	383
linux-release-arm64	OK	149
linux-release-x86_64	OK	180
windows-devel-arm64	OK	246
windows-devel-x86_64	OK	201
windows-release-arm64	OK	248
windows-release-x86_64	OK	123
wasm-release	OK	132

Exports:check_posdef chisqr covar_exp covar_exppow covar_taper distm_km distm_scaled fitAR fitAR_map fitCLS fitCLS_map fitCor fitGLS fitGLS_opt fitGLS_partition invert_chol multicore_fitGLS_partition part_csv part_data sample_partitions

Dependencies:codetools CompQuadForm doParallel foreach geosphere iterators Rcpp RcppEigen

Alaska

Rendered fromAlaska.Rmdusingknitr::rmarkdown

Last update: 2023-09-15
Started: 2023-09-15

Help page	Topics
calculate degrees of freedom for partitioned GLS	calc_dfpart
Check if a matrix is positive definite	check_posdef
Conduct a chi-squared test	chisqr
Conduct a chisqr test of "partGLS" object	chisqr.partGLS
Tapered-spherical distance-based covariance function	covar_exp covar_exppow covar_taper
Calculate cross-partition statistics in a partitioned GLS	crosspart_GLS
Calculate a distance matrix from coordinates	distm_km distm_scaled
AR regressions by REML	AR_fun fitAR
Map-level AR REML	fitAR_map
CLS for time series	fitCLS
Map-level CLS for time series	fitCLS_map
Estimate spatial parameters from time series residuals	fitCor
Fit a PARTS GLS model.	fitGLS
Fit a PARTS GLS model, with maximum likelihood spatial parameters	fitGLS_opt
Function that fitGLS_opt optimizes over	fitGLS_opt_FUN
Invert the cholesky decomposition of V	invert_chol
calculate maximum distance among a table of coordinates	max_dist
fit a parallel partitioned GLS	fitGLS_partition MCGLS_partsummary MC_GLSpart multicore_fitGLS_partition part_csv part_data
NDVI remote sensing data for 10,000 random pixels from Alaska, with rare land classes removed.	ndvi_AK10000
Find the maximum likelihood estimate of the nugget	optimize_nugget
Chisqr test for partitioned GLS	part_chisqr
Correlated t-test for paritioned GLS	part_ttest
partitioned GLS results	partGLS_ndviAK
S3 print method for "partGLS" objects	print.partGLS
S3 print method for "remoteCor" class	print.remoteCor
print method for remoteGLS	print.remoteGLS
S3 print method for remoteTS class	print.mapTS print.remoteTS smry_funM smry_funV summary.mapTS summary.remoteTS
remoteGLS constructor (S3)	remoteGLS
Randomly sample a partition matrix for partitioned GLS	sample_partitions
Conduct a t-test of "partGLS" object	t.test.partGLS
Test passing a covariance function and arguments	test_covar_fun

Package: remotePARTS 1.0.4

remotePARTS: Spatiotemporal Autoregression Analyses for Large Data Sets

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)