remove relative links

closing #659

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.
 
 </details>
 

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.
 
 </details>