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"Python 2모수 모형"의 두 판 사이의 차이

4번째 줄: 4번째 줄:
;Python 문항반응이론 2모수 모형
;Python 문항반응이론 2모수 모형


==Joint Maximum Likelihood (JML)==
<syntaxhighlight lang='python' notebook>
<syntaxhighlight lang='python' notebook>
import numpy as np
import numpy as np
12번째 줄: 13번째 줄:
estimates = girth.twopl_jml(m)
estimates = girth.twopl_jml(m)
pd.DataFrame(estimates)
pd.DataFrame(estimates)
</syntaxhighlight>
==Maximum Marginal Likelihood (MML)==
<syntaxhighlight lang='python' notebook>
import numpy as np
import pandas as pd
import girth
df = pd.read_csv("https://github.com/jmnote/zdata/raw/master/github.com/cran/ltm/data/LSAT.csv")
m = np.transpose(df.values)
estimates = girth.twopl_mml(m)
pd.DataFrame({k: estimates[k] for k in ('Difficulty','Discrimination')})
</syntaxhighlight>
</syntaxhighlight>


2021년 10월 2일 (토) 03:59 판

1 개요

Python IRT 2모수 모형
Python 문항반응이론 2PLM
Python 문항반응이론 2모수 모형

2 Joint Maximum Likelihood (JML)

import numpy as np
import pandas as pd
import girth
df = pd.read_csv("https://github.com/jmnote/zdata/raw/master/github.com/cran/ltm/data/LSAT.csv")
m = np.transpose(df.values)
estimates = girth.twopl_jml(m)
pd.DataFrame(estimates)

3 Maximum Marginal Likelihood (MML)

import numpy as np
import pandas as pd
import girth
df = pd.read_csv("https://github.com/jmnote/zdata/raw/master/github.com/cran/ltm/data/LSAT.csv")
m = np.transpose(df.values)
estimates = girth.twopl_mml(m)
pd.DataFrame({k: estimates[k] for k in ('Difficulty','Discrimination')})

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