| ci_geom_bod_intertemp {Compind} | R Documentation |
Intertemporal analysis for geometric mean quantity index numbers
Description
Intertemporal analysis for geometric mean quantity index numbers with Benefit-of-the-Doubt weights - see function ci_bod_constr.
Usage
ci_geom_bod_intertemp(x0,x1,indic_col,up_w,low_w,bench)Arguments
x0 |
A data.frame containing simple indicators - time 0 |
x1 |
A data.frame containing simple indicators - time 1 |
indic_col |
A numeric list indicating the positions of the simple indicators. |
up_w |
Weights upper bound. |
low_w |
Weights lower bound. |
bench |
Row number of the benchmark unit |
Value
An object of class "CI". This is a list containing the following elements:
ci_geom_bod_intertemp_est |
A matrix containing the Overall Change (period t1 vs t0), the Change Effect (period t1 vs t0), the Benchmark Effect (period t1 vs t0) and Weight Effect (period t1 vs t0). |
ci_method |
Method used; for this function ci_method="Intertemporal_effects_Geometric_BoD". |
Author(s)
Rogge N., Vidoli F.
References
Van Puyenbroeck T. and Rogge N. (2017) "Geometric mean quantity index numbers with Benefit-of-the-Doubt weights", European Journal of Operational Research, Volume 256, Issue 3, Pages 1004 - 1014
See Also
Examples
i1_t1 <- seq(0.3, 0.5, len = 100)
i2_t1 <- seq(0.3, 1, len = 100)
Indic_t1 = data.frame(i1_t1, i2_t1)
i1_t0 <- i1_t1 - rnorm (100, 0.2, 0.03)
i2_t0 <- i2_t1 - rnorm (100, 0.2, 0.03)
Indic_t0 = data.frame(i1_t0, i2_t0)
intertemp = ci_geom_bod_intertemp(Indic_t0,Indic_t1,c(1:2),up_w=0.95,low_w=0.05,1)
intertemp