Showing 11 of total 11 results (show query)
elipousson
mapbaltimore:Make maps for Baltimore City with open data
This package provides data from the Baltimore City, the state of Maryland, and other sources, functions to access additional data, and function to create and modify simple maps of Baltimore neighborhoods using sf and ggplot2.
Maintained by Eli Pousson. Last updated 4 months ago.
158.2 match 17 stars 3.85 score 14 scriptselipousson
bcpss:Baltimore City Public Schools
Provides access to demographic, enrollment, and survey data on Baltimore City Public School System (BCPSS).
Maintained by Eli Pousson. Last updated 1 years ago.
69.9 match 3 stars 3.48 score 5 scriptselipousson
baltimoredata:Access Updated and Historic Data on Baltimore City, Maryland
This package provides access to a small number of spatial and nonspatial datasets related to Baltimore City, Maryland.
Maintained by Eli Pousson. Last updated 8 months ago.
24.6 match 2.40 score 2 scripts
nowosad
spData:Datasets for Spatial Analysis
Diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. It includes R data of class sf (defined by the package 'sf'), Spatial ('sp'), and nb ('spdep'). Unlike other spatial data packages such as 'rnaturalearth' and 'maps', it also contains data stored in a range of file formats including GeoJSON and GeoPackage, but from version 2.3.4, no longer ESRI Shapefile - use GeoPackage instead. Some of the datasets are designed to illustrate specific analysis techniques. cycle_hire() and cycle_hire_osm(), for example, is designed to illustrate point pattern analysis techniques.
Maintained by Jakub Nowosad. Last updated 2 months ago.
datasetsrastersfspspatialspdep
3.5 match 82 stars 13.23 score 3.4k scripts 116 dependents
mrc-ide
EpiEstim:Estimate Time Varying Reproduction Numbers from Epidemic Curves
Tools to quantify transmissibility throughout an epidemic from the analysis of time series of incidence as described in Cori et al. (2013) <doi:10.1093/aje/kwt133> and Wallinga and Teunis (2004) <doi:10.1093/aje/kwh255>.
Maintained by Anne Cori. Last updated 7 months ago.
3.5 match 95 stars 12.00 score 1.0k scripts 7 dependents
alanarnholt
BSDA:Basic Statistics and Data Analysis
Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.
Maintained by Alan T. Arnholt. Last updated 2 years ago.
3.5 match 7 stars 9.11 score 1.3k scripts 6 dependents
cran
tsModel:Time Series Modeling for Air Pollution and Health
Tools for specifying time series regression models.
Maintained by Roger D. Peng. Last updated 9 months ago.
4.0 match 1 stars 3.56 score 7 dependents
markleeds2
dyn:Time Series Regression
Time series regression. The dyn class interfaces ts, irts(), zoo() and zooreg() time series classes to lm(), glm(), loess(), quantreg::rq(), MASS::rlm(), MCMCpack::MCMCregress(), quantreg::rq(), randomForest::randomForest() and other regression functions allowing those functions to be used with time series including specifications that may contain lags, diffs and missing values.
Maintained by M. Leeds. Last updated 7 years ago.
4.0 match 2.46 score 96 scripts
gpiras
hspm:Heterogeneous Spatial Models
Spatial heterogeneity can be specified in various ways. 'hspm' is an ambitious project that aims at implementing various methodologies to control for heterogeneity in spatial models. The current version of 'hspm' deals with spatial and (non-spatial) regimes models. In particular, the package allows to estimate a general spatial regimes model with additional endogenous variables, specified in terms of a spatial lag of the dependent variable, the spatially lagged regressors, and, potentially, a spatially autocorrelated error term. Spatial regime models are estimated by instrumental variables and generalized methods of moments (see Arraiz et al., (2010) <doi:10.1111/j.1467-9787.2009.00618.x>, Bivand and Piras, (2015) <doi:10.18637/jss.v063.i18>, Drukker et al., (2013) <doi:10.1080/07474938.2013.741020>, Kelejian and Prucha, (2010) <doi:10.1016/j.jeconom.2009.10.025>).
Maintained by Gianfranco Piras. Last updated 1 years ago.
3.6 match 5 stars 2.70 score 1 scriptscran
TrendSLR:Estimating Trend, Velocity and Acceleration from Sea Level Records
Analysis of annual average ocean water level time series, providing improved estimates of trend (mean sea level) and associated real-time velocities and accelerations. Improved trend estimates are based on singular spectrum analysis methods. Various gap-filling options are included to accommodate incomplete time series records. The package also includes a range of diagnostic tools to inspect the components comprising the original time series which enables expert interpretation and selection of likely trend components. A wide range of screen and plot to file options are available in the package.
Maintained by Phil J Watson. Last updated 6 years ago.
3.5 match 1.00 scorecran
msltrend:Improved Techniques to Estimate Trend, Velocity and Acceleration from Sea Level Records
Analysis of annual average ocean water level time series from long (minimum length 80 years) individual records, providing improved estimates of trend (mean sea level) and associated real-time velocities and accelerations. Improved trend estimates are based on Singular Spectrum Analysis methods. Various gap-filling options are included to accommodate incomplete time series records. The package also contains a forecasting module to consider the implication of user defined quantum of sea level rise between the end of the available historical record and the year 2100. A wide range of screen and pdf plotting options are available in the package.
Maintained by Phil J Watson. Last updated 9 years ago.
3.5 match 1.00 score 8 scripts