# Simple linear model fails

**URL:** <https://discourse.pymc.io/t/simple-linear-model-fails/5012>\
**Category:** Questions\
**Created:** [May 5, 2020, 12:21am UTC](https://discourse.pymc.io/t/simple-linear-model-fails/5012 "2020-05-05T00:21:58Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![mina](https://avatars.discourse-cdn.com/v4/letter/m/839c29/32.png) [@mina](https://discourse.pymc.io/u/mina)\
**Post date:** [May 5, 2020, 12:21am UTC](https://discourse.pymc.io/t/simple-linear-model-fails/5012/1 "2020-05-05T00:21:58Z")

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I’m trying to run a simple linear model on the famous “diamonds” dataset, but having trouble with the HMC. What am I doing wrong?

```auto
import pymc3
import numpy as np
import pandas as pd

diamonds = pd.read_csv(
    "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/diamonds.csv"
)
diamonds = diamonds.sample(n=1_000_000, replace=True)

print(diamonds)

                                                                                                                                                             
# carat cut color clarity depth table price x y z                                                                                                                                                                                   
# 38867 0.40 Premium F VS1 61.4 58.0 1050 4.75 4.73 2.91                                                                                                                                                                                   
# 18067 2.01 Fair F I1 58.7 66.0 7294 8.30 8.19 4.84                                                                                                                                                                                   
# 1507 0.71 Very Good F VS2 59.6 56.0 2994 5.84 5.88 3.49                                                                                                                                                                                   
# 6618 0.90 Premium H VS2 60.7 58.0 4082 6.21 6.17 3.76                                                                                                                                                                                   
# 39269 0.38 Premium G VS1 61.9 58.0 1069 4.66 4.62 2.87                                                                                                                                                                                   
# ... ... ... ... ... ... ... ... ... ... ...                                                                                                                                                                                   
# 5749 0.98 Very Good E SI2 61.1 60.0 3895 6.31 6.36 3.87                                                                                                                                                                                   
# 20508 1.70 Premium I VS1 61.5 58.0 8840 7.74 7.64 4.73                                                                                                                                                                                   
# 52531 0.72 Ideal I VVS2 61.7 55.0 2530 5.71 5.76 3.54                                                                                                                                                                                   
# 12146 1.00 Good E SI1 63.7 60.0 5174 6.29 6.24 3.99                                                                                                                                                                                   
# 23398 0.36 Ideal E SI1 62.0 57.0 631 4.53 4.57 2.82                                                                                                                                                                                   
                                                                                   

model = pymc3.glm.GLM.from_formula(
    "price ~ C(cut) + C(color) + C(clarity) + carat + depth + table + x + z",
    data=diamonds,
)
fit = pymc3.sample(model=model, tune=20005)

# ValueError: Mass matrix contains zeros on the diagonal.
# The derivative of RV `z`.ravel()[0] is zero.
# The derivative of RV `x`.ravel()[0] is zero.
# The derivative of RV `table`.ravel()[0] is zero.
# The derivative of RV `depth`.ravel()[0] is zero.
# The derivative of RV `carat`.ravel()[0] is zero.
# The derivative of RV `C(clarity)[T.VVS2]`.ravel()[0] is zero.
# The derivative of RV `C(clarity)[T.VVS1]`.ravel()[0] is zero.
# The derivative of RV `C(clarity)[T.VS2]`.ravel()[0] is zero.
# The derivative of RV `C(clarity)[T.VS1]`.ravel()[0] is zero.
# The derivative of RV `C(clarity)[T.SI2]`.ravel()[0] is zero.
# The derivative of RV `C(clarity)[T.SI1]`.ravel()[0] is zero.
# The derivative of RV `C(clarity)[T.IF]`.ravel()[0] is zero.
# The derivative of RV `C(color)[T.J]`.ravel()[0] is zero.
# The derivative of RV `C(color)[T.I]`.ravel()[0] is zero.
# The derivative of RV `C(color)[T.H]`.ravel()[0] is zero.
# The derivative of RV `C(color)[T.G]`.ravel()[0] is zero.
# The derivative of RV `C(color)[T.F]`.ravel()[0] is zero.
# The derivative of RV `C(color)[T.E]`.ravel()[0] is zero.
# The derivative of RV `C(cut)[T.Very Good]`.ravel()[0] is zero.
# The derivative of RV `C(cut)[T.Premium]`.ravel()[0] is zero.
# The derivative of RV `C(cut)[T.Ideal]`.ravel()[0] is zero.
# The derivative of RV `C(cut)[T.Good]`.ravel()[0] is zero.
# The derivative of RV `Intercept`.ravel()[0] is zero.
# """

```

---

<div class="post-metadata">

**Author:** ![AlexAndorra](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/alexandorra/32/9142_2.png) [@AlexAndorra](https://discourse.pymc.io/u/AlexAndorra)\
**Post date:** [May 5, 2020, 10:55am UTC](https://discourse.pymc.io/t/simple-linear-model-fails/5012/2 "2020-05-05T10:55:52Z")

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Hi Mina,  
Is your venv running with PyMC master? If yes, your issue is probably related to [this one](https://discourse.pymc.io/t/mass-matrix-contains-zeros-on-the-diagonal/4981) and you should find you answer there.  
PS: I think the GLM module uses flat priors, which can also be a cause of the error you’re experiencing.  
Hope this helps 🖖

---

<div class="post-metadata">

**Author:** ![mina](https://avatars.discourse-cdn.com/v4/letter/m/839c29/32.png) [@mina](https://discourse.pymc.io/u/mina)\
**Post date:** [May 6, 2020, 10:32pm UTC](https://discourse.pymc.io/t/simple-linear-model-fails/5012/3 "2020-05-06T22:32:54Z")

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Changing the prior fixes the issue. Thanks.