CRE: Interpretable Discovery and Inference of Heterogeneous Treatment Effects. Provides a new method for interpretable heterogeneous treatment effects characterization in terms of decision rules via an extensive exploration of heterogeneity patterns by an ensemble-of-trees approach, enforcing high stability in the discovery.

CRE is an R Package providing a flexible implementation of the Causal Rule Ensemble algorithm. Installation. Installing from CRAN.

CRE has the following features: 1. provides an interpretable representation of the HTE; 2) allows extensive exploration of com-plex heterogeneity patterns; and 3) guarantees high stability in the discovery.

一种是由四环素响应启动子元件（TRE，也叫 tetO）控制的 Cre 工具鼠（TRE-Cre，也叫 tetO-Cre）。 另一种是由组织特异性启动子驱动的表达四环素转录活化因子 rtTA 或 tTA 的小鼠。

2024年10月19日 · CRE is an R Package providing a flexible implementation of the Causal Rule Ensemble algorithm. Installation. Installing from CRAN. install.packages("CRE") Installing the latest developing version. library(devtools) install_github("NSAPH-Software/CRE", ref="develop") Import. library("CRE")

CRE is an R Package providing a flexible implementation of the Causal Rule Ensemble algorithm. Installing from CRAN. Installing the latest developing version. Import. The full list of required dependencies can be found in project in the DESCRIPTION file. y The observed response/outcome vector (binary or continuous).

2024年10月19日 · To accommodate these shortcomings, we propose Causal Rule Ensemble (CRE), a new method to discover heterogeneous subgroups through an ensemble-of-trees approach. CRE has the following features: provides an interpretable representation of the HTE; 2) allows extensive exploration of complex heterogeneity patterns; and 3) guarantees high stability ...

4 天之前 · The COVID-19 pandemic’s onset set off a once-in-a-century exogenous macroeconomic shock has left lasting scars on commercial real estate (CRE). Q2 2022 Preliminary Trend Announcement Moody’s Analytics CRE releases its Q2 2022 preliminary trend results for the apartment, office, and retail property sectors.

To accommodate these shortcomings, we propose Causal Rule Ensemble (CRE), a new method to discover heterogeneous subgroups through an ensemble-of-trees approach. CRE has the following features: provides an interpretable representation of the HTE; 2) allows extensive exploration of complex heterogeneity patterns; and 3) guarantees high stability ...

CRE has the following features: #' 1) provides an interpretable representation of the HTE; 2) allows #' extensive exploration of complex heterogeneity patterns; and 3) #' guarantees high stability in the discovery.