`normfactor`中的高斯约束

如何解决`normfactor`中的高斯约束

我想了解如何在 expected_yield 修饰符上施加具有中心值 expected_y_error 和错误 normfactor 的高斯约束。我想用单个样本 observed_data 拟合 MC_derived_sample。我的目标是提取 bu_y 修饰符，使得​​由 MC_derived_sample 缩放的 bu_y 的积分被高斯约束为 expected_yield +/- expected_y_error。

我目前的尝试使用 normsys 修饰符如下：

spec = {
    "channels": [
        {
            "name": "singlechannel","samples": [
                {
                    "name": "constrained_template","data": MC_derived_sample*expected_yield,#expect normalisation around 1
                    "modifiers": [
                        {"name": "bu_y","type": "normfactor","data": None },{"name": "bu_y_constr","type": "normsys","data": 
                                {"lo" : 1 - (expected_y_error/expected_yield),"hi" : 1 + (expected_y_error/expected_yield)} 
                        },]
                },]
        },],"observations": [
        {
            "name": "singlechannel","data": observed_data,}
    ],"measurements": [
        { 
            "name": "sig_y_extraction","config": {
                "poi": "bu_y","parameters": [
                    {"name":"bu_y","bounds": [[(1 - (5*expected_y_error/expected_yield),1+(5*expected_y_error/expected_yield)]],"inits":[1.]},]
            }
        }
    ],"version": "1.0.0"
}

我的想法是 normsys 将在由 expected_yield 缩放的样本上引入关于统一性的高斯约束。

请您就这种方法是否正确向我提供任何反馈，好吗？

此外，假设我想为 Barlow-Beeston lite 实现包含一个 staterror 修饰符，这样做是否正确？

"samples": [
                {
                    "name": "constrained_template",#expect normalisation around 1
                    "modifiers": [
                        {"name": "BB_lite_uncty","type": "staterror","data": np.sqrt(MC_derived_sample)*expected_yield },#assume poisson error and scale by central value of constraint
                        {"name": "bu_y",]
                }

非常感谢您的帮助，

布莱斯