fixing refereance to gelman book

Author: thegargiulian

README.md

@@ -97,7 +97,7 @@ de estas-. Tenga presente que al proveer un directorio la función asume las mis
 proyecto. Si usted quiere usar otras especificaciones, no debe suministrar un directorio a las estimaciones.
 
 * Por último, la función `combine_estimates` permite combinar los resultados de la estimación, lo que, una vez más, dará como
-resultado un intervalo (que incluye la media). Usa la aproximación normal usando las reglas de total expectativa y varianza. Ver sección 18.2 de [*Bayesian Data Analysis*](http://www.stat.columbia.edu/~gelman/book/) para más información.
+resultado un intervalo (que incluye la media). Usa la aproximación normal usando las reglas de total expectativa y varianza. Ver sección 18.2 de [*Bayesian Data Analysis*](https://sites.stat.columbia.edu/gelman/book/) para más información.
 
 ## Agradecimientos
 Agradecemos a [Micaela Morales](https://github.com/mmazul) por su atenta prueba beta.

inst/docs/README-en.md

@@ -90,7 +90,7 @@ To use this package, it is necessary to have previously downloaded the data from
 
 * The `mse` function allows you to make estimates of underreporting using [LCMCR](https://doi.org/10.1111/biom.12502) specification (see Section 6 of the [methodological report](https://www.comisiondelaverdad.co/sites/default/files/descargables/2022-08/04_Anexo_Proyecto_JEP_CEV_HRDAG_08022022.pdf)). To use this function, you need to define stratification variables and apply the stratification (i.e., by grouping the data according to these variables). See the function's example and Section 8.4.2 of the [methodological report](https://www.comisiondelaverdad.co/sites/default/files/descargables/2022-08/04_Anexo_Proyecto_JEP_CEV_HRDAG_08022022.pdf)). These estimates take time and computational resources to run. If you would like to make use of the estimates already calculated by our team, you'll need to download the estimates from the [Truth Commission website](https://www.comisiondelaverdad.co/analitica-de-datos-informacion-y-recursos#c3) onto your local machine. You can make use of the pre-calculated estimates by specifying the path to the `estimates_dir` argument.  Keep in mind that by providing a directory, the function assumes the same specifications for the model used in the project. If you want to use other specifications, don't provide a directory to the estimates.
 
-* Finally, the `combine_estimates` function allows you to combine the results of the estimation, yielding an approximate 95% credibility interval and the point estimate of the mean of the total number of victims in a stratum of interest including both the uncertainty from the missing data imputation and from the multiple systems estimation model. The function uses the Normal approximation using the laws of total expectation and total variance. See Section 18.2 of [*Bayesian Data Analysis*](http://www.stat.columbia.edu/~gelman/book/) for more information.
+* Finally, the `combine_estimates` function allows you to combine the results of the estimation, yielding an approximate 95% credibility interval and the point estimate of the mean of the total number of victims in a stratum of interest including both the uncertainty from the missing data imputation and from the multiple systems estimation model. The function uses the Normal approximation using the laws of total expectation and total variance. See Section 18.2 of [*Bayesian Data Analysis*](https://sites.stat.columbia.edu/gelman/book/) for more information.
 
 ## Acknowledgments
 We thank [Micaela Morales](https://github.com/mmazul) for her thoughtful beta testing of the package.