If statement 如何相对于Ox中的另一个变量为变量分配可选值(有点类似于C+;+;) 我用Ox(语法类似C、C++和java)模拟一些数据,我被困在分配部分。比方说,我有一个模拟我的数据的函数,g_my: decl g_mX, g_mY; simuldata(const ct) // ct : number of observations { decl mx = ranbinomial(ct, 1, 1, 0.40)~ 100*ranu(ct, 1); decl veps = rann(ct, 1); decl vp = < .0485434;-.006764 ; -.0187657; -1.106632 ; .3647326 ; 1.11204 >; g_mX = mx[][0:1] ; // regressors: Gender, Age. decl cut1 = vp[2], cut2 = vp[3], cut3 = vp[4], cut4 = vp[5] ; decl Yt = g_mX*vp[:1] + veps ; // latent variable decl g_mX,g_mY; simuldata(const-ct)//ct:观察次数 { decl mx=ranu(ct,1,1,0.40)~100*ranu(ct,1); decl veps=rann(ct,1); decl vp=; g_mX=mX[][0:1];//回归系数:性别、年龄。 decl cut1=vp[2],cut2=vp[3],cut3=vp[4],cut4=vp[5]; decl Yt=g_mX*vp[:1]+veps;//潜变量
我想做的是使用上面定义的切点(cut…)和潜在变量(Yt)创建g_mY,并计算g_mY的替代值。更像这样:If statement 如何相对于Ox中的另一个变量为变量分配可选值(有点类似于C+;+;) 我用Ox(语法类似C、C++和java)模拟一些数据,我被困在分配部分。比方说,我有一个模拟我的数据的函数,g_my: decl g_mX, g_mY; simuldata(const ct) // ct : number of observations { decl mx = ranbinomial(ct, 1, 1, 0.40)~ 100*ranu(ct, 1); decl veps = rann(ct, 1); decl vp = < .0485434;-.006764 ; -.0187657; -1.106632 ; .3647326 ; 1.11204 >; g_mX = mx[][0:1] ; // regressors: Gender, Age. decl cut1 = vp[2], cut2 = vp[3], cut3 = vp[4], cut4 = vp[5] ; decl Yt = g_mX*vp[:1] + veps ; // latent variable decl g_mX,g_mY; simuldata(const-ct)//ct:观察次数 { decl mx=ranu(ct,1,1,0.40)~100*ranu(ct,1); decl veps=rann(ct,1); decl vp=; g_mX=mX[][0:1];//回归系数:性别、年龄。 decl cut1=vp[2],cut2=vp[3],cut3=vp[4],cut4=vp[5]; decl Yt=g_mX*vp[:1]+veps;//潜变量,if-statement,conditional-statements,rounding,simulation,ox,If Statement,Conditional Statements,Rounding,Simulation,Ox,我想做的是使用上面定义的切点(cut…)和潜在变量(Yt)创建g_mY,并计算g_mY的替代值。更像这样: g_mY = new matrix[rows(g_mX)][1] ; // dependent variable for(decl i = 0; i < rows(g_mX); ++i) { if(Yt[i] < cut1) { g_mY[i] = &
g_mY = new matrix[rows(g_mX)][1] ; // dependent variable
for(decl i = 0; i < rows(g_mX); ++i)
{
if(Yt[i] < cut1)
{
g_mY[i] = < a number between 1 and 100, but != to a multiple of 5 >
}
else if(Yt[i]> cut1 .&& Yt[i]<= cut2)
{
g_mY[i] = 5 || g_mY[i] = 15 || g_mY[i] = 35 || g_mY[i] = 45 || g_mY[i] = 55 ||
g_mY[i] = 65 || g_mY[i] = 85 || g_mY[i] = 95 ;
// one of these multiples of 5 that are not multiples of 10
}
else if(Yt[i]> cut2 .&& Yt[i] <= cut3)
{
g_mY[i] = 10 || g_mY[i] = 20 || g_mY[i] = 30 || g_mY[i] = 40 ||
g_mY[i] = 60 || g_mY[i] = 70 || g_mY[i] = 80 || g_mY[i] = 90 ;
// one of these multiples of 10
}
else if(Yt[i] > cut3 .&& Yt[i] <= cut4)
{
g_mY[i] = 25 || g_mY[i] = 75 ; //either 25 or 75
}
else if(Yt[i] > cut4)
{
g_mY[i] = 50 || g_mY[i] = 100; //either 50 or 100
}
}
return 1
}
g_mY=new matrix[rows(g_mX)][1];//因变量
对于(decli=0;i
}
否则,如果(Yt[i]>cut1.&Yt[i]cut2.&Yt[i]cut3.&Yt[i]cut4)
{
g|mY[i]=50 | g|mY[i]=100;//50或100
}
}
返回1
}
当我打印g_mY时,我只有零。我怎样才能成功地做到这一点
非常感谢。如果我正确理解了您的问题,下面的代码应该可以回答。它显示了几种随机选取变量的方法:使用循环(#1)、使用函数
ranindex
(#2)或使用三元运算符(#3)
#包括
#包括
decl g_mX,g_mY;
simuldata(常数ct){//ct:观测次数
decl mx=ranu(ct,1,1,0.40)~100*ranu(ct,1);
decl veps=rann(ct,1);
decl vp=<.0485434;-.006764;-.0187657;-1.106632;.3647326;1.11204>;
g_mX=mX[][0:1];//回归系数:性别、年龄。
decl cut1=vp[2],cut2=vp[3],cut3=vp[4],cut4=vp[5];
decl Yt=g_mX*vp[:1]+veps;//潜变量
g_mY=新矩阵[行(g_mX)][1];//因变量
对于(decli=0;icut1.&Yt[i];
g_mY[i]=ar[ranindex(1,行(ar))];/#2
}如果(Yt[i]>cut2.&&Yt[i],如果您能发布一个最低限度的工作示例,说明您必须能够复制您的问题并帮助解决问题,这将非常有用。这正是我想要的。非常感谢Malick,您太棒了!
#include <oxstd.oxh>
#include <oxprob.h>
decl g_mX, g_mY;
simuldata(const ct) { // ct : number of observations
decl mx = ranbinomial(ct, 1, 1, 0.40)~ 100 * ranu(ct, 1);
decl veps = rann(ct, 1);
decl vp = < .0485434; -.006764 ; -.0187657; -1.106632 ; .3647326 ; 1.11204 >;
g_mX = mx[][0:1] ; // regressors: Gender, Age.
decl cut1 = vp[2], cut2 = vp[3], cut3 = vp[4], cut4 = vp[5] ;
decl Yt = g_mX * vp[:1] + veps ; // latent variable
g_mY = new matrix[rows(g_mX)][1] ; // dependent variable
for (decl i = 0; i < rows(g_mX); ++i) {
if (Yt[i] < cut1) {
decl temp ;
do { //#1
temp = 1 + ranindex(1, 100);
} while (imod(temp, 5) == 0); // a number between 1 and 100, but != to a multiple of 5
g_mY[i] = temp ;
} else if (Yt[i] > cut1 .&& Yt[i] <= cut2) {
decl ar = < 5; 15; 35; 45; 55; 65; 85; 95 >;
g_mY[i] = ar[ranindex(1, rows(ar))] ;//#2
} else if (Yt[i] > cut2 .&& Yt[i] <= cut3) {
decl ar = range(10,90,10)'; // == < 10; 20; 30; 40; 60; 70; 80; 90 >;
g_mY[i] = ar[ranindex(1, rows(ar))] ;//#2
} else if (Yt[i] > cut3 .&& Yt[i] <= cut4) {
g_mY[i] = ranu(1, 1) > 0.5 ? 25 : 75 ;//#3
} else if (Yt[i] > cut4) {
g_mY[i] = ranu(1, 1) > 0.5 ? 50 : 100 ;//#3
}
}
return 1;
}
main() {
simuldata(100);
println(g_mY);
}