From 21f7b39c4924d0f59c6a2cd2015b4051fe8720ab Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 8 May 2024 10:19:06 +0100 Subject: [PATCH] remove relative links closing #659 --- README.Rmd | 16 ++++++++-------- README.md | 40 +++++++++++++++++++--------------------- 2 files changed, 27 insertions(+), 29 deletions(-) diff --git a/README.Rmd b/README.Rmd index 499edb52f..6723fe1e4 100644 --- a/README.Rmd +++ b/README.Rmd @@ -35,11 +35,11 @@ Uncertainty is propagated from all inputs into the final parameter estimates, he `{EpiNow2}` provides three models: -* [`estimate_infections()`](reference/estimate_infections.html): Reconstruct cases by date of infection from reported cases. +* `estimate_infections()`: Reconstruct cases by date of infection from reported cases. -* [`estimate_secondary()`](reference/estimate_secondary.html): Estimate the relationship between primary and secondary observations, for example, deaths (secondary) based on hospital admissions (primary), or bed occupancy (secondary) based on hospital admissions (primary). +* `estimate_secondary()`: Estimate the relationship between primary and secondary observations, for example, deaths (secondary) based on hospital admissions (primary), or bed occupancy (secondary) based on hospital admissions (primary). -* [`estimate_truncation()`](reference/estimate_truncation.html): Estimate a truncation distribution from multiple snapshots of the same data source over time. For more flexibility, check out the [`{epinowcast}`](https://package.epinowcast.org/) package. +* `estimate_truncation()`: Estimate a truncation distribution from multiple snapshots of the same data source over time. For more flexibility, check out the [`{epinowcast}`](https://package.epinowcast.org/) package. The default model in `estimate_infections()` uses a non-stationary Gaussian process to estimate the time-varying reproduction number and infer infections. Other options, which generally reduce runtimes at the cost of the granularity of estimates or real-time performance, include: @@ -52,17 +52,17 @@ The default model in `estimate_infections()` uses a non-stationary Gaussian proc * A deconvolution/back-calculation method for inferring infections, followed with calculating the time-varying reproduction number. * Adjustment for the remaining susceptible population beyond the forecast horizon. -The documentation for [`estimate_infections`](reference/estimate_infections.html) provides examples of the implementation of the different options available. +The documentation for `estimate_infections` provides examples of the implementation of the different options available. `{EpiNow2}` is designed to be used via a single function call to two functions: -* [`epinow()`](reference/epinow.html): Estimate Rt and cases by date of infection and forecast these infections into the future. +* `epinow()`: Estimate Rt and cases by date of infection and forecast these infections into the future. -* [`regional_epinow()`](reference/regional_epinow.html): Efficiently run `epinow()` across multiple regions in an efficient manner. +* `regional_epinow()`: Efficiently run `epinow()` across multiple regions in an efficient manner. -These two functions call [`estimate_infections()`](reference/estimate_infections.html), which works to reconstruct cases by date of infection from reported cases. +These two functions call `estimate_infections()`, which works to reconstruct cases by date of infection from reported cases. -For more details on using each function see the [function documentation](reference/index.html). +For more details on using each function corresponding function documentation. diff --git a/README.md b/README.md index bd2a85628..c75521923 100644 --- a/README.md +++ b/README.md @@ -59,17 +59,17 @@ Models provided `{EpiNow2}` provides three models: -- [`estimate_infections()`](reference/estimate_infections.html): - Reconstruct cases by date of infection from reported cases. +- `estimate_infections()`: Reconstruct cases by date of infection from + reported cases. -- [`estimate_secondary()`](reference/estimate_secondary.html): Estimate - the relationship between primary and secondary observations, for - example, deaths (secondary) based on hospital admissions (primary), or - bed occupancy (secondary) based on hospital admissions (primary). +- `estimate_secondary()`: Estimate the relationship between primary and + secondary observations, for example, deaths (secondary) based on + hospital admissions (primary), or bed occupancy (secondary) based on + hospital admissions (primary). -- [`estimate_truncation()`](reference/estimate_truncation.html): - Estimate a truncation distribution from multiple snapshots of the same - data source over time. For more flexibility, check out the +- `estimate_truncation()`: Estimate a truncation distribution from + multiple snapshots of the same data source over time. For more + flexibility, check out the [`{epinowcast}`](https://package.epinowcast.org/) package. The default model in `estimate_infections()` uses a non-stationary @@ -90,25 +90,23 @@ cost of the granularity of estimates or real-time performance, include: - Adjustment for the remaining susceptible population beyond the forecast horizon. -The documentation for -[`estimate_infections`](reference/estimate_infections.html) provides -examples of the implementation of the different options available. +The documentation for `estimate_infections` provides examples of the +implementation of the different options available. `{EpiNow2}` is designed to be used via a single function call to two functions: -- [`epinow()`](reference/epinow.html): Estimate Rt and cases by date of - infection and forecast these infections into the future. +- `epinow()`: Estimate Rt and cases by date of infection and forecast + these infections into the future. -- [`regional_epinow()`](reference/regional_epinow.html): Efficiently run - `epinow()` across multiple regions in an efficient manner. +- `regional_epinow()`: Efficiently run `epinow()` across multiple + regions in an efficient manner. -These two functions call -[`estimate_infections()`](reference/estimate_infections.html), which -works to reconstruct cases by date of infection from reported cases. +These two functions call `estimate_infections()`, which works to +reconstruct cases by date of infection from reported cases. -For more details on using each function see the [function -documentation](reference/index.html). +For more details on using each function corresponding function +documentation.