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Create Contour Plots from Data or a Function
Provides functions for making contour plots. The contour plot can be created from grid data, a function, or a data set. If non-grid data is given, then a Gaussian process is fit to the data and used to create the contour plot.
Modeling Animal Movement with Continuous-Time Discrete-Space Markov Chains
Software to facilitates taking movement data in xyt format and pairing it with raster covariates within a continuous time Markov chain (CTMC) framework. As described in Hanks et al. (2015)
Maximum Likelihood Shrinkage using Generalized Ridge or Least Angle Regression
Functions are provided to calculate and display ridge TRACE Diagnostics for a
variety of alternative Shrinkage Paths. While all methods focus on Maximum Likelihood
estimation of unknown true effects under normal distribution-theory, some estimates are
modified to be Unbiased or to have "Correct Range" when estimating either [1] the noncentrality
of the F-ratio for testing that true Beta coefficients are Zeros or [2] the "relative" MSE
Risk (i.e. MSE divided by true sigma-square, where the "relative" variance of OLS is known.)
The eff.ridge() function implements the "Efficient Shrinkage Path" introduced in Obenchain
(2022)
A LazyData Facility
Supplies a LazyData facility for packages which have data sets but do not provide LazyData: true. A single function is is included, requireData, which is a drop-in replacement for base::require, but carrying the additional functionality. By default, it suppresses package startup messages as well. See argument 'reallyQuitely'.
Doubly Robust Distribution Balancing Weighting Estimation
Implements the doubly robust distribution balancing weighting proposed by Katsumata (2024)
Mark-Recapture Distance Sampling
Animal abundance estimation via conventional, multiple covariate and mark-recapture distance sampling (CDS/MCDS/MRDS). Detection function fitting is performed via maximum likelihood. Also included are diagnostics and plotting for fitted detection functions. Abundance estimation is via a Horvitz-Thompson-like estimator.
Data Analysis and Graphics Data and Functions
Functions and data sets used in examples and exercises in the text Maindonald, J.H. and Braun, W.J. (2003, 2007, 2010) "Data Analysis and Graphics Using R", and in an upcoming Maindonald, Braun, and Andrews text that builds on this earlier text.
Interactive Grammar of Graphics
An implementation of an interactive grammar of graphics, taking the best parts of 'ggplot2', combining them with the reactive framework of 'shiny' and drawing web graphics using 'vega'.
Compute Scagnostics on Pairs of Numeric Variables in a Data Set
Computes a range of scatterplot diagnostics (scagnostics) on pairs
of numerical variables in a data set. A range of scagnostics, including graph
and association-based scagnostics described by Leland Wilkinson and Graham
Wills (2008)
Miscellaneous Functions for Working with 'stars' Rasters
Miscellaneous functions for working with 'stars' objects, mainly single-band rasters. Currently includes functions for: (1) focal filtering, (2) detrending of Digital Elevation Models, (3) calculating flow length, (4) calculating the Convergence Index, (5) calculating topographic aspect and topographic slope.