"Python 2모수 모형"의 두 판 사이의 차이

2021년 10월 6일 (수) 19:36 기준 최신판

1 개요[ | ]

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

2 JML[ | ]

Joint Maximum Likelihood(JML) Method

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 MML[ | ]

Maximum Marginal Likelihood(MML) Method

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 ('Discrimination','Difficulty')})

4 같이 보기[ | ]

@@ 4번째 줄: / 4번째 줄: @@
 ;Python 문항반응이론 2모수 모형
-==Joint Maximum Likelihood (JML)==
+==JML==
+* [[Joint Maximum Likelihood]](JML) Method
 <syntaxhighlight lang='python' notebook>
 import numpy as np
@@ 15번째 줄: / 16번째 줄: @@
 </syntaxhighlight>
-==Maximum Marginal Likelihood (MML)==
+==MML==
-<syntaxhighlight lang='python' notebook>
+* [[Maximum Marginal Likelihood]](MML) Method
+<syntaxhighlight lang='python' notebook=mml>
 import numpy as np
 import pandas as pd