FHDI-package {FHDI} | R Documentation |
Fractional Hot Deck Imputation
Description
Perform fractional hot deck imputation or perform fully efficient fractional imputation. This package is partially supported by the NSF grant CSSI 1931380.
Details
FHDI_Driver(daty, datr=NULL, datz=NULL, s_op_imputation="FEFI", i_op_SIS=0, s_op_SIS="global", s_op_cellmake="knn", top_corr_var=100, i_op_variance=1, M=5, k=5, w=NULL, id=NULL, s_op_merge="fixed", categorical=NULL)
Author(s)
Author: Inho Cho [aut, cre], Jaekwang Kim [aut], Jongho Im [aut], Yicheng Yang [aut] icho@iastate.edu
References
Im, J., Cho, I.H. and Kim, J.K. (2018). FHDI: An R Package for Fractional Hot-Deck Imputation. The R Journal. 10(1), pp. 140-154; Im, J., Kim, J.K. and Fuller, W.A. (2015). Two-phase sampling approach to fractional hot deck imputation, Proceeding of the Survey Research Methods Section, Americal Statistical Association, Seattle, WA.
See Also
FHDI_CellMake and FHDI_CellProb
Examples
### Toy Example ###
# y : multi-variate vector
# r : indicator corresponding to missingness in y
set.seed(1345)
n=100
rho=0.5
e1=rnorm(n,0,1)
e2=rnorm(n,0,1)
e3=rgamma(n,1,1)
e4=rnorm(n,0,sd=sqrt(3/2))
y1=1+e1
y2=2+rho*e1+sqrt(1-rho^2)*e2
y3=y1+e3
y4=-1+0.5*y3+e4
r1=rbinom(n,1,prob=0.6)
r2=rbinom(n,1,prob=0.7)
r3=rbinom(n,1,prob=0.8)
r4=rbinom(n,1,prob=0.9)
y1[r1==0]=NA
y2[r2==0]=NA
y3[r3==0]=NA
y4[r4==0]=NA
daty=cbind(y1,y2,y3,y4)
result_FEFI=FHDI_Driver(daty, s_op_imputation="FEFI", k=3)
result_FHDI=FHDI_Driver(daty, s_op_imputation="FHDI", M=5, k=3)
result_FHDI_merging=FHDI_Driver(daty, s_op_imputation="FHDI", s_op_cellmake="merging", M=5, k=3)
FEFI_SIS=FHDI_Driver(daty, i_op_SIS=2, s_op_SIS="intersection", k=3)
names(result_FEFI)
names(result_FHDI)
names(result_FHDI_merging)
names(FEFI_SIS)