Regress_FTest
在1-alpha的置信水平下，方程线性关系的置信检验：F检验；返回的结果是一个数组，第一个数为F统计值，二为p值，三为原假设的值（0表示拒绝，1表示接受） F-检验统计量： [img type="tslxml" file="media2024-03-20_WEfCpvnqqtg5qGJa/image556.png"][/img] 其中：RSS是残差平方和，即[img type="tslxml" file="media2024-03-20_WEfCpvnqqtg5qGJa/image557.png"][/img]； ESS是回归平方和，因变量的拟合值与因变量均值的差的平方，即[img type="tslxml" file="media2024-03-20_WEfCpvnqqtg5qGJa/image558.png"][/img]； TSS是总平方和 TSS=RSS+ESS； 原假设：[img type="tslxml" file="media2024-03-20_WEfCpvnqqtg5qGJa/image559.png"][/img]([img type="tslxml" file="media2024-03-20_WEfCpvnqqtg5qGJa/image560.png"][/img]为方程的系数)表示回归方程不显著；
范例(t):
[code]
U:=array(0.245863,0.056726,-0.145411,-0.287547,-0.410684,0.012821,0.073042,0.201905,…
来源于.NET函数大全
Regression
范例(t):
[code]
Y:=array(0.001,0.564,0.193,0.809,0.585,0.48,0.35,0.896,0.823,0.747);
X:= array(
(0…
Regress_FTest
范例(t):
[code]
U:=array(0.245863,0.056726,-0.145411,-0.287547,-0.410684,0.012821,0.073042,0.201905,…
Regress_TTest
范例(t):


[code]


U:=array(0.245863,0.056726,-0.145411,-0.287547,-0.410684,-0.012821,0.073042,…
Regress_JBTest
范例(t):
[code]
Y:=array(0.564,0.693,0.809,0.985,1.18,1.896,2.3,2.747,3);
return regress_jbtest(y,0…