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In the vignette "Handle Missing Values with brms", section "Imputation before model fitting", there are m = 5 multiply imputed datasets used for mixing their posterior draws. However, according to the…
ghost updated
5 years ago
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I’m very interested in using your R-package MixSIAR in my research that focuses on vegetation source water identification. I have a few questions and I’m just wondering if I may request your guidance …
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Hi Brian
I have run a model with a continuous effect (length in cm); DIC values indicate that this is the best fit model in my case. I am however confused by the model output - see isospace and pos…
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I am trying to implement a logistic multinomial regression (AKA softmax regression). In this example I am trying to classify the iris dataset.
I have a problem specifying the model, I get an optimiza…
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Submitting Author: Dom Bennett (@dombennett)
Repository: https://github.com/AntonelliLab/outsider
Version submitted: 0.0.0
Editor: @annakrystalli
Reviewer 1: @nuest
Reviewer 2: @hrbrms…
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In `Stan`, there is an option to write a `generated quantities` block for sample generation. Doing the similar in pymc3, however, seems to introduce weird turbulence to the sampler, especially if the …
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#### Summary:
Split the current manual into multiple documents. This in part mirrors how we're going to split the repos into a Stan language and Stan algorithms repo.
##### Reference Manual
* …
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[edited 12/17/2018 with new keywords]
#### Summary:
Support syntax:
```
real beta;
```
The "unconstrained" variable `x` is transformed to the "constrained" variable
```
y = mu + x * …
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```julia
using Turing
@model gdemo(x) = begin
s ~ InverseGamma(2,3)
m ~ Normal(0,sqrt(s))
x[1] ~ Normal(m, sqrt(s))
x[2] ~ Normal(m, sqrt(s))
return s, m
end
g = gdemo([1.5, 2])…
yebai updated
5 years ago
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* Operating System: WIndows 10
* brms Version: 2.4.0
Hi,
I hope it's okay to post this here. I'm trying to determine which variables explain the variation in a binary outcome (divorce yes/no) a…