diff options
Diffstat (limited to 'src/ubms-vignette.Rmd')
| -rw-r--r-- | src/ubms-vignette.Rmd | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/src/ubms-vignette.Rmd b/src/ubms-vignette.Rmd index 8d328e3..870a6c7 100644 --- a/src/ubms-vignette.Rmd +++ b/src/ubms-vignette.Rmd @@ -22,7 +22,7 @@ knitr::opts_chunk$set(message=FALSE, warning=FALSE) ## What is ubms? -`ubms` is an R package for fitting models of wildlife occurrence and abundance to with datasets where animals are not individually marked. +`ubms` is an R package for fitting models of wildlife occurrence and abundance with datasets where animals are not individually marked. It provides a nearly identical interface to the popular `unmarked` package [@Fiske_2011]. Instead of using maximum likelihood to fit models (as with `unmarked`), models are fit in a Bayesian framework using [Stan](https://mc-stan.org/) [@Carpenter_2017]. @@ -150,7 +150,7 @@ options(mc.cores=3) ```{r, echo=FALSE} library(ubms) -(fit_stan <- stan_occu(~1~1, data=umf, chains=3, iter=500, refresh=0)) +(fit_stan <- stan_occu(~1~1, data=umf, chains=3, iter=1000, refresh=0)) ``` ### Compare results @@ -232,13 +232,13 @@ fit_global <- stan_occu(~scale(date)~scale(forest)+scale(ele), data=umf, ```{r, echo=FALSE} fit_null <- fit_stan fit_sc <- stan_occu(~1~scale(forest)+scale(ele), data=umf, - chains=3, iter=500, refresh=0) -fit_oc <- stan_occu(~scale(date)~1, data=umf, chains=3, iter=500, refresh=0) + chains=3, iter=1000, refresh=0) +fit_oc <- stan_occu(~scale(date)~1, data=umf, chains=3, iter=1000, refresh=0) ``` ```{r, warning=TRUE, echo=FALSE} fit_global <- stan_occu(~scale(date)~scale(forest)+scale(ele), data=umf, - chains=3, iter=500, refresh=0) + chains=3, iter=1000, refresh=0) ``` The `fit_global` model gave us some warnings about the effective sample size (`n_eff`) along with a suggested solution. |