Add to vignette

vignettes/model-description.Rmd

@@ -548,6 +548,17 @@ The mean is $(1-p) \cdot \mu_{1} + p \cdot \mu_{2}$ and the variance is $(1-p) ^
 Here, and for the other mixture distributions, the probability of the larger mean can be obtained from `plogis(fit$model$par[["logit_p_mix"]])` and the ratio of the larger mean to the smaller mean can be obtained from `1 + exp(fit$model$par[["log_ratio_mix"]])`.
 The standard errors are available in the TMB sdreport: `fit$sd_report`.
 
+If you wish to fix the probability of a large (i.e., extreme) mean, which can be hard to estimate, you can use the `map` list. E.g.:
+
+```r
+sdmTMB(...,
+  control = sdmTMBcontrol(
+    start = list(logit_p_mix = qlogis(0.05)), # 5% probability of 'mu2'
+    map = list(logit_p_mix = factor(NA)) # don't estimate
+  )
+)
+```
+
 Example: `family = gamma_mix(link = "log")`. See also `family = delta_gamma_mix()` for an extension incorporating this distribution with delta models.
 
 ## Lognormal mixture