def random_effect( df , group , X_cols , Y_cols ):
"""
変量効果モデル(※ではない。今後修正)
"""
fixed = _convert( df=df , group=group )
params = {}
for key , value in fixed.items():
X = lib.df2mat( df=value , columns=X_cols )
Y = lib.df2mat( df=value , columns=Y_cols )
b = lib.reg( X=X , Y=Y )
params[key] = b
return params
import lib
import sys
import numpy as np
"""
6 Inference2
"""
lib.title("#############6 Inference2#############")
#####データを読み取る#####
HPRICE_dataset = lib.load(filename="HPRICE1.csv")
explanatories = ["const", "sqrft", "bdrms"]
explained = ["lprice"]
#####各変数を定義#####
X = lib.df2mat(df=HPRICE_dataset, columns=explanatories)
Y = lib.df2mat(df=HPRICE_dataset, columns=explained)
b = lib.reg(X=X, Y=Y)
"""
6-1の解答
"""
lib.chaper("<6.1の解答>")
#####解答#####
lib.add_suffix(b, labels=explanatories)
print("\n")
"""
6-2の解答
"""
lib.chaper("<6.2の解答>")
#####回帰係数の取得#####
const, sqrft, bdrms = b[0], b[1], b[2]
y_bdrms = bdrms