imputeMissValues: Impute missing covariate values

In KevinSee/qRfish: Estimate carrying capacity with quantile regression forests

Description

filter rows with too many missing values, and imputes the remaining missing values.

Usage

imputeMissValues(data = NULL, covariates = NULL,
  imputation_metrics = NULL, max_miss = 3, response = NA, ntree = 1000)

Arguments

data	data.frame containing the response metric, the covariates and any other imputation metrics
covariates	character vector of names of covariates to be used in QRF model
imputation_metrics	character vector of names of additional covariates to be used in imputing missing values in the covariates.
max_miss	maximum number of missing covariate values for any given data point. Data points with more than this number of missing values will be deleted.
response	column name of response value

Value

data.frame with response vector in first column and covariates in subsequent columns.

Author(s)

Kevin See

Examples

imputeMissValues(data = mod_data, covariates = hab_mets, imputation_metrics = impute_mets, response = 'chnk_per_m')

KevinSee/qRfish documentation built on May 8, 2019, 4:50 p.m.