# Why does the MAP estimate of the parameter vector of the dirichlet sum to 1?
**URL:** https://discourse.pymc.io/t/why-does-the-map-estimate-of-the-parameter-vector-of-the-dirichlet-sum-to-1/858
**Category:** Questions
**Created:** [February 13, 2018, 9:13pm UTC](https://discourse.pymc.io/t/why-does-the-map-estimate-of-the-parameter-vector-of-the-dirichlet-sum-to-1/858 "2018-02-13T21:13:50Z")
**Posts on this page:** 3
**Page:** 1
### Author:  [@abhicherath](https://discourse.pymc.io/u/abhicherath)
#### Post date: [February 13, 2018, 9:13pm UTC](https://discourse.pymc.io/t/why-does-the-map-estimate-of-the-parameter-vector-of-the-dirichlet-sum-to-1/858/1 "2018-02-13T21:13:51Z")
```
#Example for Pymc3 forums
import pymc3 as pm
import theano.tensor as tt
import pandas as pd
import numpy as np
pred_arr = [[2,3,4],[5,1,9]]
data = [2,3]
with pm.Model() as model:
a_vec = np.array([100 for i in range(3)])
prior = pm.Dirichlet('a',a = a_vec,shape=(3))
likelihood = pm.Normal('y',mu = tt.dot(np.array(pred_arr),prior),sd = 0.1,observed = np.array(data).T)
abra = pm.find_MAP()
trace = pm.fit(1000,start = abra)
```
In the above example of dirichlet regression (note the numbers are just nonsense), I don’t understand why the posterior values of the concentration parameters of the dirichlet sum to 1. Why is this?
EDIT: I am very sorry, my brain had a massive derp. obviously the MAP values are not the MAPs of the concentration parameters, rather the actual values for which the posterior is maxed. Please close this.
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### Author:  [@junpenglao](https://discourse.pymc.io/u/junpenglao)
#### Post date: [February 14, 2018, 6:22am UTC](https://discourse.pymc.io/t/why-does-the-map-estimate-of-the-parameter-vector-of-the-dirichlet-sum-to-1/858/2 "2018-02-14T06:22:13Z")
No problem 😉 Thumbs up for finding out the solution/reason yourself.
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### Author:  [@junpenglao](https://discourse.pymc.io/u/junpenglao)
#### Post date: [February 14, 2018, 6:22am UTC](https://discourse.pymc.io/t/why-does-the-map-estimate-of-the-parameter-vector-of-the-dirichlet-sum-to-1/858/3 "2018-02-14T06:22:16Z")