Gauss and matlab: A comparison
GAUSS 与 MATLAB:一项比较AI 解读 ↓
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GAUSS 与 MATLAB:一项比较AI 解读 ↓
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Abstract I compare two high‐level matrix programming languages with built‐in function libraries and graphics routines. Their interactive nature and convenient syntax makes them ideal for use in econometric applications. The languages are remarkably similar in terms of their features and performance. MATLAB's chief advantage is that it runs on a wider array of hardware and operating systems than GAUSS. GAUSS's main advantage is that it has better coverage of statistical and econometric routines. Overall, MATLAB's features seem best suited for analysing time‐series data and other macro econometric applications, while GAUSS is ideal for analysing panel data and other microeconometric applications.
通过状态空间边际化高效进行动态结构方程模型的贝叶斯估计
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将 Prais–Winsten 回归扩展至高阶自回归误差面板:模拟研究
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无限阶面板自回归过程的工具变量估计
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动态潜在类别结构方程模型:密集纵向数据建模实操教程
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考虑时间结构的合成控制
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迭代边际化贝叶斯映射进行似然最大化及其非线性面板模型应用
Complex dynamic systems can be investigated by fitting mechanistic stochastic dynamic models to time series data. In this context, commonly used Monte Carlo inference procedures for model selection and parameter estimation quickly become computationally unfeasible as the system dimension grows. The increasing prevalence of panel data, characterized by multiple related time series, therefore necessitates the development of inference algorithms that are effective for this…