Description Usage Arguments Value Author(s) Examples
filter rows with too many missing values, and imputes the remaining missing values.
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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 |
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 |
data.frame with response vector in first column and covariates in subsequent columns.
Kevin See
1 | imputeMissValues(data = mod_data, covariates = hab_mets, imputation_metrics = impute_mets, response = 'chnk_per_m')
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