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swash (version 1.1.0)

confint-methods: Methods for Function confint

Description

Methods for function confint

Arguments

Methods

signature(object = "sbm", iterations = 100, samples_ratio = 0.8, alpha = 0.05, replace = TRUE)

Creates bootstrap confidence intervals for sbm objects. The argument iterations indicates the number of bootstrap samples which are drawn. Since the initial data in the Swash-Backwash Model should be balanced, entity-based bootstrap sampling is carried out. This means that not, for example, 80% of all observations are included in each sample at a sample ratio equal to \(p\) = 0.8 (samples_ratio = 0.8), but rather all observations for 80% of the regions. The significance level for the confidence intervals \(\alpha\) is set by the argument alpha (default: 0.05, which corresponds to a 95% confidence level).

Author

Thomas Wieland

References

Swash-Backwash Model:

Cliff AD, Haggett P (2006) A swash-backwash model of the single epidemic wave. Journal of Geographical Systems 8(3), 227-252. tools:::Rd_expr_doi("https://doi.org/10.1007/s10109-006-0027-8")

Smallman-Raynor MR, Cliff AD, Stickler PJ (2022) Meningococcal Meningitis and Coal Mining in Provincial England: Geographical Perspectives on a Major Epidemic, 1929–33. Geographical Analysis 54, 197–216. tools:::Rd_expr_doi("https://doi.org/10.1111/gean.12272")

Smallman-Raynor MR, Cliff AD, The COVID-19 Genomics UK (COG-UK) Consortium (2022) Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020–December 2021. Epidemiology and Infection 150, e145. tools:::Rd_expr_doi("https://doi.org/10.1017/S0950268822001285").

Bootstrapping und bootstrap confidence intervals:

Efron B, Tibshirani RJ (1993) An Introduction to the Bootstrap.

Ramachandran KM, Tsokos CP (2021) Mathematical Statistics with Applications in R (Third Edition). Ch. 13.3.1 (Bootstrap confidence intervals). tools:::Rd_expr_doi("https://doi.org/10.1016/B978-0-12-817815-7.00013-0")

See Also

sbm_ci-class