[QuantEcon]MATLAB混编FORTRAN语言

$$
\begin{aligned}
VAR(y_t|y_{t-1},\ldots,y_1)&= VAR(E(y_t|\theta_t,y_{t-1},\ldots,y_1)|y_{t-1},\ldots,y_1)\\
&+ E(VAR(y_t|\theta_t,y_{t-1},\ldots,y_1)|y_{t-1},\ldots,y_1)\\
&= VAR(E(y_t|\theta_t)| y_{t-1},\ldots,y_1) + E(VAR(y_t|\theta_t)|y_{t-1},\ldots,y_1) .
\end{aligned}
$$

Ver ist das.
Schön ,


$$
\left[
\hat{\theta} = \arg\min_\theta \bar{g}(\theta)'\big[\hat{\Omega}(\theta)\big]^{-1}\bar{g}(\theta)
\right]
$$

Given some regularity conditions, the GMM estimator converges as $n$ goes to infinity to the following distribution:
$$
\left[
\sqrt{n}(\hat{\theta}-\theta_0) \stackrel{L}{\rightarrow} N(0,V),
\right]
$$
where

$$
\left[
V = E\left(\frac{\partial g(\theta_0,x_i)}{\partial\theta}\right)'\Omega(\theta_0)^{-1}E\left(\frac{\partial g(\theta_0,x_i)}{\partial\theta}\right)
\right]
$$
Inference can therefore be performed on $\hat{\theta}$ using the assumption that it is approximately distributed as $N(\theta_0,\hat{V}/n)$.  

c.d.f

$$
G(w(p))  = \frac{ \int_{\underline p}^p d \Gamma(x) }{\int_{\underline p}^{\bar p} d \Gamma(x) }
.
$$