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Interface Between R and the OpenStreetMap-Based Routing Service OSRM
An interface between R and the 'OSRM' API. 'OSRM' is a routing service based on 'OpenStreetMap' data. See < http://project-osrm.org/> for more information. This package enables the computation of routes, trips, isochrones and travel distances matrices (travel time and kilometric distance).
Optimal Exact Tests for Multiple Binary Endpoints
Calculates exact hypothesis tests to compare a treatment and a reference group with respect to multiple binary endpoints. The tested null hypothesis is an identical multidimensional distribution of successes and failures in both groups. The alternative hypothesis is a larger success proportion in the treatment group in at least one endpoint. The tests are based on the multivariate permutation distribution of subjects between the two groups. For this permutation distribution, rejection regions are calculated that satisfy one of different possible optimization criteria. In particular, regions with maximal exhaustion of the nominal significance level, maximal power under a specified alternative or maximal number of elements can be found. Optimization is achieved by a branch-and-bound algorithm. By application of the closed testing principle, the global hypothesis tests are extended to multiple testing procedures.
Calculate the Care Density or Fragmented Care Density Given a Patient-Sharing Network
Given a patient-sharing network, calculate either the classic care density as
proposed by Pollack et al. (2013)
Confounder-Adjusted Survival Curves and Cumulative Incidence Functions
Estimate and plot confounder-adjusted survival curves using
either 'Direct Adjustment', 'Direct Adjustment with Pseudo-Values',
various forms of 'Inverse Probability of Treatment Weighting', two
forms of 'Augmented Inverse Probability of Treatment Weighting',
'Empirical Likelihood Estimation' or 'Targeted Maximum Likelihood Estimation'.
Also includes a significance test for the difference
between two adjusted survival curves and the calculation of adjusted
restricted mean survival times. Additionally enables the user to
estimate and plot cause-specific confounder-adjusted cumulative
incidence functions in the competing risks setting using the same
methods (with some exceptions).
For details, see Denz et. al (2023)
Open GenBank Files
Opens complete record(s) with .gb extension from the NCBI/GenBank Nucleotide database and returns a list containing shaped record(s). These kind of files contains detailed records of DNA samples (locus, organism, type of sequence, source of the sequence...). An example of record can be found at < https://www.ncbi.nlm.nih.gov/nuccore/HE799070>.
Datasets for "Statistics: UnLocking the Power of Data"
Datasets for the third edition of "Statistics: Unlocking the Power of Data" by Lock^5 Includes version of datasets from earlier editions.
Imputation of High-Dimensional Count Data using Side Information
Analysis, imputation, and multiple imputation of count data using covariates. LORI uses a log-linear Poisson model where main row and column effects, as well as effects of known covariates and interaction terms can be fitted. The estimation procedure is based on the convex optimization of the Poisson loss penalized by a Lasso type penalty and a nuclear norm. LORI returns estimates of main effects, covariate effects and interactions, as well as an imputed count table. The package also contains a multiple imputation procedure. The methods are described in Robin, Josse, Moulines and Sardy (2019)
The Symmetric Group: Permutations of a Finite Set
Manipulates invertible functions from a finite set to
itself. Can transform from word form to cycle form and
back. To cite the package in publications please use
Hankin (2020) "Introducing the permutations R package",
SoftwareX, volume 11
The Hyperdirichlet Distribution, Mark 2
A suite of routines for the hyperdirichlet distribution
and reified Bradley-Terry; supersedes the 'hyperdirichlet' package;
uses 'disordR' discipline
Exploratory Data Analysis for the 'spatstat' Family
Functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.