Sum of residuals of scipy regression model - python-3.x

Question

I am going through a stats workbook with python, there is a practice hands on question on which i am stuck. Its related to Poisson regression and here is the problem statement:-
Perform the following tasks:
Load the R data set Insurance from MASS package and Capture the data as pandas data frame
Build a Poisson regression model with a log of an
independent variable, Holders and dependent variable Claims.
Fit the model with data.
Find the sum of residuals.
I am stuck with point 4 above. Can anyone help with this step?
Here is what i have done so far :-
import statsmodels.api as sm
import statsmodels.formula.api as smf
import numpy as np
df = sm.datasets.get_rdataset('Insurance', package='MASS', cache=False).data
poisson_model = smf.poisson('np.log(Holders) ~ -1 + Claims', df)
poisson_result = poisson_model.fit()
print(poisson_result.summary())
Now how to get sum of residuals?

Answer 1

np.sum(poisson_result.resid)
works fine
You have used the wrong variables to build the poisson model as pointed out by Karthikeyan.
Use this instead,
poisson_model = smf.poisson('Claims ~ np.log(Holders)',df)

Answer 2

Try below code for Fresco play
import statsmodels.api as sm
import statsmodels.formula.api as smf
import pandas as pd
import numpy as np
df_insurance=sm.datasets.get_rdataset("Insurance","MASS")
df_data=df_insurance.data
insurance_model=smf.poisson('Claims ~ np.log(Holders)', df_data).fit()
print(np.cumsum(insurance_model.resid))

Answer 3

1.a) Load the R data set Insurance from MASS package
1.b) and Capture the data as pandas data frame
2) Build a Poisson regression model with a log of an independent variable, Holders and dependent variable Claims.
3) Fit the model with data.
4) Find the sum of residuals.
import statsmodels.api as sm
import statsmodels.formula.api as smf
import pandas as pd
import numpy as np
#load the R data set insurrance from MASS package
ins = sm.datasets.get_rdataset('Insurance','MASS').data
# capture the data as pandas data frame
ins_pd = pd.DataFrame(ins)
# build a poisson regressions model with
# a log of an independent variable "Holders"
# and dependent variable "Claims"
# fit the model with data
result = smf.poisson('Claims ~ np.log(Holders)',data=ins).fit()
# you can also use
# model = smf.poisson('Claims ~ np.log(Holders)',data=ins)
# result = model.fit()
# Find tue sum of residuals
print('Sum ot the residuals:',np.sum(result.resid))
i'm new on this so i don't know if capture the data as panda dataframe is fine or not but letme now
greetings

Answer 4

Fresco Mex
import statsmodels.api as sm
import statsmodels.formula.api as smf
import pandas as pd
import numpy as np
df_data=sm.datasets.get_rdataset("Insurance","MASS").data
df_dataf= pd.DataFrame(df_data)
insurance_model=smf.poisson('Claims ~ np.log(Holders)',df_data)
insurance_model_result=insurance_model.fit()
print(np.sum(insurance_model_result.resid))

Answer 5

in the poisson_model = smf.poisson('np.log(Holders) ~ -1 + Claims', df) statement, the dependent variable "Claims" should come in the right hand side
poisson_model = smf.poisson('Claims ~ np.log(Holders)-1 ', df)

Answer 6

this qualified in "Fresco" if anyone is looking for the solution
df_insurance=sm.datasets.get_rdataset("Insurance","MASS")
df_data=df_insurance.data
insurance_model=smf.poisson('Claims ~ np.log(Holders)',df_data)
insurance_model_result=insurance_model.fit()
res=(insurance_model_result.resid)
print(np.sum(res))

Answer 7

I don't know it will work or not .but I refer this docs
https://vincentarelbundock.github.io/Rdatasets/doc/MASS/Insurance.html
https://vincentarelbundock.github.io/Rdatasets/datasets.html
So I hope this will work too.
import statsmodels.api as sm
import statsmodels.formula.api as smf
import numpy as np
import pandas as pd
data=pd.DataFrame(sm.datasets.get_rdataset("Insurance","MASS",cache=True).data)
model=smf.poisson('Claims ~ District + Group + Age + np.log(Holders)',data).fit()
print(np.sum(model.resid))

Answer 8

Try np.cumsum(model.resid) for this question.
Ideally np.sum(model.resid) should be the right answer for the question... But if the system is not accepting it, try the cumsum