target.arrival.dea: Arrival target setting using DEA
In DJL: Distance Measure Based Judgment and Learning

target.arrival.dea

R Documentation

Arrival target setting using DEA

Description

Employs dm.dea over time to estimate the arrival of known specifications.

Usage

target.arrival.dea(xdata, ydata, date, t, rts="crs", orientation, 
                   sg="ssm", ftype="d", ncv=NULL, env=NULL, cv="convex", anc=FALSE)

Arguments

`xdata`	Input(s) vector (n by m)
`ydata`	Output(s) vector (n by s)
`date`	Production date (n by 1)
`t`	A vantage point from which the RoC is captured
`rts`	Returns to scale assumption `"crs"` Constant RTS (default) `"vrs"` Variable RTS `"irs"` Increasing RTS `"drs"` Decreasing RTS
`orientation`	Orientation of the measurement `"i"` Input-orientation `"o"` Output-orientation
`sg`	Employs second-stage optimization `"ssm"` Slack-sum maximization (default) `"max"` Date-sum maximization `"min"` Date-sum minimization
`ftype`	Frontier type `"d"` Dynamic frontier (default) `"s"` Static frontier
`ncv`	Non-controllable variable index(binary) for internal NDF (1 by (m+s))
`env`	Environment index for external NDF (n by 1)
`cv`	Convexity assumption `"convex"` Convexity holds (default) `"fdh"` Free disposal hull (this will override `rts`)
`anc`	Implements a stepwise RoC computation if `TRUE`

Value

`$eff_t`	Efficiency at `t`
`$lambda_t`	Intensity vector at `t`
`$eft_date`	Effective date
`$roc_avg`	Average RoC
`$roc_anc`	Local RoCs across the periods
`$roc_local`	Local RoC
`$roc_ind`	Individualized RoC
`$arrival_avg`	Estimated arrival using `roc_avg`
`$arrival_seg`	Estimated arrival using `roc_ind`

Author(s)

Dong-Joon Lim, PhD

References

Lim, Dong-Joon, Timothy R. Anderson, and Oliver Lane Inman. "Choosing effective dates from multiple optima in Technology Forecasting using Data Envelopment Analysis (TFDEA)." Technological Forecasting and Social Change 88 (2014): 91~97.

Lim, Dong-Joon, and Timothy R. Anderson. Time series benchmarking analysis for new product scheduling: who are the competitors and how fast are they moving forward?. Advances in DEA Theory and Applications: with Examples in Forecasting Models. (2017): 443-458.

Examples

# Reproduce Table 4 in Lim, D-J., and Timothy R. Anderson.(2016)
  # Load airplane dataset
  df <- dataset.airplane.2017
  
  # ready
  x <- data.frame(Flew = rep(1, 28))
  y <- subset(df, select = 3 : 7)
  d <- subset(df, select = 2)

  # go
  target.arrival.dea(x, y, d, 2007, "vrs", "o", "min", "d")$arrival_seg

DJL documentation built on March 31, 2023, 9:05 p.m.