SimEval {imputeR}

Evaluate imputation performance by simulation

Description

Evaluate imputation performance by simulation

Usage

SimEval(data, task = NULL, p = 0.1, n.sim = 100, ini = "mean",
  method = NULL, guess = FALSE, guess.method = NULL, other = NULL,
  verbose = TRUE, seed = 1234)

Arguments

data

is the complete data matrix that will be used for simulation

task

task type, either be 1 for regression, 2 for classification or 3 for mixed type

p

is the percentage of missing values that will be introduction into data, it has to be a value between 0 and 1

n.sim

the number of simulations, default is 100 times

ini

is the initialization setting for some relevant imputation methods , the default setting is "mean", while "median" and "random" can also be used. See also guess

method

the imputaion method based on variable selection for simulation some other imputation method can be passed to the 'other' argument

guess

logical value, if is TRUE, then guess will be used as the imputation method for simulation

guess.method

guess type for the guess function. It cannot be NULL if guess is TRUE

other

some other imputation method that is based on variable selection can be used. The requirement for this 'other' method is strict: it receives a data matrix including missing values and returns a complete data matrix.

verbose

logical, if TRUE, additional output information will be provided during iterations, i.e., the method that is using, the iteration number, the convegence difference as compared to the precious iteration. The progression bar will show up irrespective of this option and it can not be got rid of.

seed

set the seed for simulation so simulations using different imputation methods are comparable. The default value is set to 1234, which is not supposed to mean anything. But if 1234 is used, then the seed for simulating the first missing data matrix is 1234, then it sums by one for every subsequent simulationg data matrix.

Value

a list of componentes including

call

the method used for imputation

task

the name of the task

time

computational time

error

the imputation error

conv

the number of iterations to converge

Examples

data(parkinson)
# WARNING: simulation may take considerable time.

SimEval(parkinson, method = "lassoR")