Package: SSN2 0.2.1
Michael Dumelle
SSN2: Spatial Modeling on Stream Networks
Spatial statistical modeling and prediction for data on stream networks, including models based on in-stream distance (Ver Hoef, J.M. and Peterson, E.E., (2010) <doi:10.1198/jasa.2009.ap08248>.) Models are created using moving average constructions. Spatial linear models, including explanatory variables, can be fit with (restricted) maximum likelihood. Mapping and other graphical functions are included.
Authors:
SSN2_0.2.1.tar.gz
SSN2_0.2.1.zip(r-4.5)SSN2_0.2.1.zip(r-4.4)SSN2_0.2.1.zip(r-4.3)
SSN2_0.2.1.tgz(r-4.4-x86_64)SSN2_0.2.1.tgz(r-4.4-arm64)SSN2_0.2.1.tgz(r-4.3-x86_64)SSN2_0.2.1.tgz(r-4.3-arm64)
SSN2_0.2.1.tar.gz(r-4.5-noble)SSN2_0.2.1.tar.gz(r-4.4-noble)
SSN2_0.2.1.tgz(r-4.4-emscripten)SSN2_0.2.1.tgz(r-4.3-emscripten)
SSN2.pdf |SSN2.html✨
SSN2/json (API)
NEWS
| # Install 'SSN2' in R: |
| install.packages('SSN2', repos = c('https://usepa.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/usepa/ssn2/issues
- mf04p - Imported SSN object from the MiddleFork04.ssn data folder
Last updated 3 months agofrom:ab39f126e2. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 27 2024 |
| R-4.5-win-x86_64 | OK | Oct 27 2024 |
| R-4.5-linux-x86_64 | OK | Oct 27 2024 |
| R-4.4-win-x86_64 | OK | Oct 27 2024 |
| R-4.4-mac-x86_64 | OK | Oct 27 2024 |
| R-4.4-mac-aarch64 | OK | Oct 27 2024 |
| R-4.3-win-x86_64 | OK | Oct 27 2024 |
| R-4.3-mac-x86_64 | OK | Oct 27 2024 |
| R-4.3-mac-aarch64 | OK | Oct 27 2024 |
Exports:AICcaugmentcopy_lsn_to_tempcovmatrixcreate_netgeomdispersion_initialdispersion_paramseuclid_initialeuclid_paramsglanceglancesloocvnugget_initialnugget_paramspseudoR2randcov_initialrandcov_paramsssn_create_distmatssn_get_datassn_get_netgeomssn_get_stream_distmatssn_glmssn_importssn_import_predptsssn_lmssn_namesssn_put_datassn_rbetassn_rbinomssn_rgammassn_rinvgaussssn_rnbinomssn_rnormssn_rpoisssn_simulatessn_split_predptsssn_subsetSSN_to_SSN2ssn_update_pathssn_writetaildown_initialtaildown_paramstailup_initialtailup_paramstidyTorgegramvarcomp
Dependencies:bitbit64blobcachemclassclassIntclicpp11DBIe1071fansifastmapgenericsglueKernSmoothlatticelifecyclemagrittrMASSMatrixmemoisepillarpkgconfigplogrproxyRcpprlangRSQLites2sfspmodeltibbleunitsutf8vctrswithrwk
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute AIC and AICc of fitted model objects | AIC.SSN2 AIC.ssn_glm AIC.ssn_lm AICc.ssn_glm AICc.ssn_lm |
| Compute analysis of variance and likelihood ratio tests of fitted model objects | anova.SSN2 anova.ssn_glm anova.ssn_lm tidy.anova.ssn_glm tidy.anova.ssn_lm |
| Augment data with information from fitted model objects | augment.SSN2 augment.ssn_glm augment.ssn_lm |
| Extract fitted model coefficients | coef.SSN2 coef.ssn_glm coef.ssn_lm coefficients.ssn_glm coefficients.ssn_lm |
| Confidence intervals for fitted model parameters | confint.SSN2 confint.ssn_glm confint.ssn_lm |
| Compute Cook's distance | cooks.distance.SSN2 cooks.distance.ssn_glm cooks.distance.ssn_lm |
| Copy LSN to temporary directory | copy_lsn_to_temp |
| Create a covariance matrix | covmatrix.SSN2 covmatrix.ssn_glm covmatrix.ssn_lm |
| Create netgeom column in SSN object | create_netgeom |
| Fitted model deviance | deviance.SSN2 deviance.ssn_glm deviance.ssn_lm |
| Extract model fitted values | fitted.SSN2 fitted.ssn_glm fitted.ssn_lm fitted.values.ssn_glm fitted.values.ssn_lm |
| Model formulae | formula.SSN2 formula.ssn_glm formula.ssn_lm |
| Glance at a fitted model object | glance.SSN2 glance.ssn_glm glance.ssn_lm |
| Glance at many fitted model objects | glances.SSN2 glances.ssn_glm glances.ssn_lm |
| Compute leverage (hat) values | hatvalues.SSN2 hatvalues.ssn_glm hatvalues.ssn_lm |
| Regression diagnostics | influence.SSN2 influence.ssn_glm influence.ssn_lm |
| Find labels from object | labels.SSN2 labels.ssn_glm labels.ssn_lm |
| Extract log-likelihood | logLik.SSN2 logLik.ssn_glm logLik.ssn_lm |
| Perform leave-one-out cross validation | loocv.SSN2 loocv.ssn_glm loocv.ssn_lm |
| Imported SSN object from the MiddleFork04.ssn data folder | mf04p |
| MiddleFork04.ssn: Middle Fork 2004 stream temperature dataset | MiddleFork04.ssn |
| Extract the model frame from a fitted model object | model.frame.SSN2 model.frame.ssn_glm model.frame.ssn_lm |
| Extract the model matrix from a fitted model object | model.matrix.SSN2 model.matrix.ssn_glm model.matrix.ssn_lm |
| Plot fitted model diagnostics | plot.SSN2 plot.ssn_glm plot.ssn_lm |
| Plot Torgegram | plot.Torgegram |
| Model predictions (Kriging) | predict.SSN2 predict.ssn_glm predict.ssn_lm |
| Print SSN object | print.SSN |
| Print values | print.anova.ssn_glm print.anova.ssn_lm print.SSN2 print.ssn_glm print.ssn_lm print.summary.ssn_glm print.summary.ssn_lm |
| Compute a pseudo r-squared | pseudoR2.SSN2 pseudoR2.ssn_glm pseudoR2.ssn_lm |
| Extract fitted model residuals | resid.ssn_glm resid.ssn_lm residuals.SSN2 residuals.ssn_glm residuals.ssn_lm rstandard.ssn_glm rstandard.ssn_lm |
| Calculate Hydrologic Distances for an 'SSN' object | ssn_create_distmat |
| Get a data.frame from an SSN, ssn_lm, or ssn_glm object | ssn_get_data |
| Extract netgeom column | ssn_get_netgeom |
| Get stream distance matrices from an 'SSN' object | ssn_get_stream_distmat |
| Fitting Generalized Linear Models for Spatial Stream Networks | ssn_glm |
| Import 'SSN' object | ssn_import |
| Import prediction points into an SSN, ssn_lm, or ssn_glm object | ssn_import_predpts |
| Create a covariance parameter initial object | euclid_initial nugget_initial ssn_initial taildown_initial tailup_initial |
| Fitting Linear Models for Spatial Stream Networks | ssn_lm |
| Return names of data in an SSN object | ssn_names |
| Create covariance parameter objects. | euclid_params nugget_params ssn_params taildown_params tailup_params |
| Put an sf data.frame in an SSN object | ssn_put_data |
| Simulate random variables on a stream network | ssn_rbeta ssn_rbinom ssn_rgamma ssn_rinvgauss ssn_rnbinom ssn_rnorm ssn_rpois ssn_simulate |
| Split a prediction dataset in an 'SSN' object | ssn_split_predpts |
| Subset an 'SSN' object | ssn_subset |
| Convert object from 'SpatialStreamNetwork' class to 'SSN' class | SSN_to_SSN2 |
| Update path in an SSN object | ssn_update_path |
| write an SSN object | ssn_write |
| Summarize an SSN object | summary.SSN |
| Summarize a fitted model object | summary.SSN2 summary.ssn_glm summary.ssn_lm |
| Tidy a fitted model object | tidy.SSN2 tidy.ssn_glm tidy.ssn_lm |
| Compute the empirical semivariogram | Torgegram |
| Variability component comparison | varcomp.SSN2 varcomp.ssn_glm varcomp.ssn_lm |
| Calculate variance-covariance matrix for a fitted model object | vcov.SSN2 vcov.ssn_glm vcov.ssn_lm |
