We propose a new quadratic-programming-based method of approximating a nonstandard density using a multivariate Gaussian density. Such nonstandard densities usually arise while developing posterior samplers for unobserved components models involving inequality constraints on the parameters. For instance, Chat et al. (2016) propose a new model of trend inflation with linear inequality constraints on the stochastic trend. We implement the proposed new method for this model and compare it to the existing approximation. We observe that the proposed new method works as good as the existing approximation in terms of the final trend estimates while achieving greater gains in terms of sample efficiency.

翻译：我们提出一种新的基于二次-方案拟定方法,使用多变量高斯密度,接近非标准密度,这种非标准密度通常出现,同时为未观察到的参数受不平等限制的部件模型开发后方取样器。例如,查特等人(2016年)提出了新的趋势通货膨胀模式,对悬浮趋势实行线性不平等限制。我们实施了这一模式的拟议新方法,并将其与现有的近似值进行比较。我们发现,拟议的新方法在最终趋势估计值方面与现有近似值一样有效,同时在抽样效率方面取得更大收益。