PRIME_SimuData

prime_SimuData
An Example of Simulated Data for PRIME

datasets

Partial Replacement Imputation Estimation (PRIME) can overcome problems caused by missing covariates in additive partially linear model. PRIME conducts imputation and regression simultaneously with known and unknown model structure. More details can be referred to
Zishu Zhan, Xiangjie Li and Jingxiao Zhang. (2022) <arXiv:2205.14994>.

Zishu Zhan

misPRIME

Partial Replacement Imputation Estimation for Missing Covariates

Xiangjie Li

Jingxiao Zhang

PRIME_SimuData function

The dataset prime_SimuData contains n = 200 samples with p = 8 covariates with missing<dl class="dl-horizontal">
<dt>Y</dt><dd>the response</dd>
<dt>X</dt><dd>the covariates with missing data</dd>
</dl>

Format

prime_SimuData
An Example of Simulated Data for PRIME — PRIME_SimuData

The dataset prime_SimuData contains n = 200 samples with p = 8 covariates with missing<dl class='dl-horizontal'>
<dt>Y</dt><dd>the response</dd>
<dt>X</dt><dd>the covariates with missing data</dd>
</dl>

PRIME_SimuData: prime_SimuData An Example of Simulated Data for PRIME

Description

Usage

Arguments

Format