My data like this:
plot | canopy | date | item | value |
---|---|---|---|---|
20 | ho | May | ppfd | 0.29279095 |
19 | ho | May | ppfd | 0.123954839 |
43 | ho | May | ppfd | 0.259633055 |
44 | ho | May | ppfd | 0.251543658 |
10 | bu | May | ppfd | 0.102567214 |
9 | bu | May | ppfd | 0.099152069 |
34 | bu | May | ppfd | 0.092671325 |
33 | bu | May | ppfd | 0.099522834 |
12 | bu | May | ppfd | 0.09847836 |
and I fitted a very simple model using brms
fit_lightquatum_may<-brm(formula=value~canopy+(1|plot),
family = gaussian(link="identity"),
data=data_lightquatum_may,
seed=1,
prior=c(set_prior("",class="Intercept"),
set_prior("",class="sigma")),
chains=4,
iter=50000,
warmup=20000,
thin=1,
control = list(adapt_delta=0.99,max_treedepth = 15,stepsize=0.001) )
I want to compare the values between bu and ho, and try to plot the results like this:
I got all variables used this : get_variables(fit_lightquatum_may)
But I can not found the value of estimate (mean?) and 95% credible intervals of bu,
How can I found the estimate value of bu?
Thank you very much!