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snowboot (version 1.0.2)

Bootstrap Methods for Network Inference

Description

Functions for analysis of network objects, which are imported or simulated by the package. The non-parametric methods of analysis center on snowball and bootstrap sampling for estimating functions of network degree distribution. For other parameters of interest, see, e.g., 'bootnet' package.

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Version

Install

install.packages('snowboot')

Monthly Downloads

188

Version

1.0.2

License

GPL-3

Maintainer

Vyacheslav Lyubchich

Last Published

April 25th, 2020

Functions in snowboot (1.0.2)

lsmi_union

Snowball Sampling with Multiple Inclusions around Several Subsets of Seeds
sample_about_one_seed

Snowball Sampling with Multiple Inclusions around One Network Node
vertboot

Bootstrapping a Network with Vertex Bootstrap
lsmi_dd

Network Degree Distribution Estimated from Labeled Snowball Sample with Multiple Inclusion (LSMI)
plot.snowboot

Plot Degree Distribution Estimates
lsmi_cv

Cross-validation to Select an Optimal Combination of n.seed and n.wave
artificial_networks

10 Simulated Networks of Order 2000 with Polylogarithmic (0.1, 2) Degree Distributions
lsmi

Labeled Snowball with Multiple Inclusions (LSMI)
boot_dd

Bootstrapping Empirical Degree Distribution
boot_ci

Confidence Intervals from Bootstrapped Network Degree Distribution
random_network

Construct Artificial Networks
igraph_to_network

Create a "Network" Object from an igraph Object